ML OPS
TALENT SOLUTIONS
Our MLOP's recruitment services are specifically tailored to the field of Machine Learning Operations. We understand the critical role ML Ops professionals play in bridging the gap between machine learning development and operational deployment, ensuring scalable, efficient, and reliable machine learning systems.
We specialize in MLOPS Jobs, offering data talent solutions for all levels of seniority within ML Ops, from hands-on engineers to strategic leaders. Our comprehensive approach ensures that your team not only has the technical expertise to manage ML systems but also the vision to achieve operational excellence and innovation.
WHY
HARNHAM?
Our reputation as a global leader in data recruitment is built on a foundation of hundreds of dedicated specialists who operate across the United States, Europe, and the United Kingdom. This extensive network empowers us to offer unparalleled recruitment solutions, matching our clients with the ideal Machine Learning Engineering and MLOPs Jobs talent.
We recognize the unique nature of each organization's Machine Learning needs. Our recruitment strategies are, therefore, highly customized, focusing on understanding and aligning with your specific business objectives and technical requirements.
OUR
SERVICES
- Permanent and Contract Recruitment: We provide both permanent and contract recruitment solutions, ensuring flexibility to meet the evolving needs of your Machine Learning projects and initiatives, including MLOPs jobs.
- Executive Search: Our executive search service is designed to identify and secure leaders in the Machine Learning field who can propel your business strategies and technological innovations forward.
- Industry-Specific Expertise: We operate across all industries, offering specialized recruitment solutions that understand and cater to the unique challenges and opportunities within your sector.
Contact us today to learn how our bespoke talent solutions can enhance your organization's Machine Learning capabilities.
JOBS
LATEST ML OPS
JOBS
Harnham are a specialist Data & AI recruitment business with teams that only focus on niche areas.
Senior Data Engineer (IC)
London
£80000 - £90000
+ Data Engineering
PermanentLondon
To Apply for this Job Click Here
Senior Data Engineer (IC)
Location: Remote (Office in London and Wiltshire)
Salary: Up to £90,000 + Benefits
This is an exciting opportunity to join a growing organisation and take ownership of a greenfield data platform. You will play a key role in shaping engineering standards, building scalable pipelines, and enabling the analytics and insight capabilities that will underpin the company’s next stage of growth.
The Company
They are a well established organisation providing essential services across both public and private sectors. Following significant expansion, they are investing heavily in modern data capabilities to improve operational performance and deliver better outcomes for the communities they support. Their technology function is scaling quickly, giving you the opportunity to make a genuine impact in a developing data environment.
The Role
As a Senior Data Engineer, you will have responsibilities for:
- Own the delivery of core data products including pipelines, curated datasets, and models.
- Design and enhance scalable data architecture to improve reliability and performance.
- Build and maintain ETL and ELT pipelines using SQL, Python, and cloud technologies.
- Champion engineering best practices including CI/CD, documentation, and observability.
- Develop trusted datasets and metrics used across analytics and reporting teams.
- Work closely with stakeholders across Data, Product, and Leadership to translate requirements into robust data solutions.
- Support the organisation’s move toward MLOps‑ready platforms and processes.
Your Skills and Experience
You will be required to have experience in the following tools:
- Strong commercial experience building and maintaining production‑grade ETL and ELT pipelines.
- Advanced SQL and Python skills for modelling, transformation, and optimisation.
- Hands‑on experience with cloud data tooling such as Azure, AWS, or GCP.
- A solid understanding of data engineering principles including quality, reliability, and automation.
- Experience working within modern engineering environments, ideally with CI/CD and containerisation.
- Exposure to orchestration, observability, and analytics engineering is beneficial but not essential.
What They Offer
- Fully remote working with occasional monthly travel.
- A chance to shape a greenfield data platform in a growing tech function.
- Opportunities for progression across Data Engineering, MLOps, and DevOps practices.
How to Apply
If this sounds like the next step in your data engineering career, please apply with your CV!
To Apply for this Job Click Here
Principal Machine Learning Engineer – ML Platform
$200000 - $230000
+ Data Science & AI
PermanentUSA
To Apply for this Job Click Here
Principal Machine Learning Engineer – ML Platform
REMOTE – US
$180,000-$230,000 + Equity
We’re partnered with a scaling AI‑driven technology company building large‑scale, production‑grade ML systems used in real‑time decisioning. They’re seeking a Senior Machine Learning Engineer who loves production ML over research, with an emphasis on distributed compute, reliability, and end‑to‑end ownership.
This is a role for someone who enjoys shaping platform architecture while still being hands‑on.
What you’ll be doing
- Designing, training, and deploying high‑scale ML models used in live systems
- Building distributed training pipelines (PyTorch, Ray)
- Owning the ML lifecycle across feature engineering, training, evaluation, inference, monitoring
- Improving ML reliability, observability, and reproducibility
- Working closely with engineering, SRE, and product to shape platform direction
- Contributing to ML architecture standards, CI/CD, and testing frameworks
What they’re looking for
- Strong experience delivering production ML systems end‑to‑end
- Expertise with Python, PyTorch, distributed compute (Ray, Spark)
- Background in large‑scale data processing and MLOps tooling
- Ability to diagnose production issues and drive architectural improvements
- Experience with event‑driven ML and model deployment frameworks is a plus
Why this role
- High ownership of ML platform direction
- Complex, real‑world ML workloads at meaningful scale
- Opportunity to improve and evolve existing infrastructure
- Equity + strong compensation package
HOW TO APPLY
If you’re passionate about building robust, scalable ML systems that drive real business impact, apply now.
To Apply for this Job Click Here
AI Engineer
London
£70000 - £80000
+ Data Science & AI
PermanentLondon
To Apply for this Job Click Here
AI Engineer
London, hybrid working (2-3 days per week in the office)
Up to 80,000 base plus 10 percent bonus and benefits
If you want to build meaningful AI products, work with modern tooling, and shape how a fast‑growing consumer brand uses data, this role gives you the autonomy, variety, and technical challenge to step up and make visible impact.
The Company
They are a high‑growth consumer brand with a strong digital presence and millions of active users. Their success has been driven by innovative tech, data‑driven decision making, and a commitment to enhancing customer experience through personalisation. You will join a business that invests heavily in AI and gives engineers the space to deliver production‑ready solutions that genuinely move the needle.
The Role
As an AI Engineer, you will work across GenAI and traditional ML, delivering end‑to‑end solutions that improve both customer experience and internal operations.
Key responsibilities include:
* Building GenAI features for customer‑facing products, including conversational and visual experiences.
* Applying LLMs to internal automation projects that unlock significant time savings across the business.
* Engineering scalable pipelines and services for supervised and unsupervised ML models, including recommenders, forecasting, and segmentation.
* Collaborating closely with data scientists, engineers, and product teams to design and deploy production‑ready solutions.
* Working within a cloud‑native environment and contributing to a modern AI and ML engineering stack.
Your Skills and Experience
* Strong commercial experience with Python and familiarity with cloud‑native development, ideally GCP.
* Ability to explain technical concepts clearly and work collaboratively with non‑technical teams.
* Experience applying AI or ML in real product or workflow settings.
* Solid understanding of core ML engineering principles and production best practices.
* A STEM degree and a genuine interest in AI innovation.
* Comfortable working in an environment where you have autonomy but also clear processes to follow.
What They Offer
* Up to 85,000 base salary plus 10 percent bonus.
* Hybrid working with flexibility; Thursdays on site are required.
* A benefits package including product discounts, wellbeing perks, life assurance, and additional lifestyle rewards.
* A role where you will work across GenAI, deep learning, MLOps, and recommender systems.
* The chance to have a significant impact in a lean, high‑performing team during an exciting growth phase.
How to Apply
If you are interested in this AI Engineer role, please apply with your CV and we will be in touch.
To Apply for this Job Click Here
Founding AI Engineer
San Francisco
$250000 - $300000
+ Data Science & AI
PermanentSan Francisco, California
To Apply for this Job Click Here
Founding AI Engineer
San Francisco, CA (Hybrid/On‑site preferred)
Founding Team * Full‑Time
$250,000-$300,000 salary + equity
About the Role
I’m looking for a hands‑on Founding AI Engineer to build and ship the core AI systems that will drive the product forward. Your work will center on fine‑tuning large language models, designing and owning training pipelines, and deploying models that perform reliably in real‑world production environments.
This role is ideal for someone who loves building: running experiments, writing code, optimizing models, and taking features from early prototype to fully deployed. You’ll work directly with me, help define our technical direction, and make an outsized impact from day one.
What You’ll Do
- Fine‑tune and adapt leading LLMs (OpenAI, Claude, Llama, Mistral, OSS) for production use cases.
- Build hands‑on data pipelines for SFT, DPO, LoRA, RL methods, and synthetic data generation.
- Design evaluation systems to measure accuracy, reliability, grounding, and hallucination reduction.
- Develop high‑performance inference infrastructure (quantization, batching, GPU optimization).
- Own the full lifecycle of ML features: modeling → pipelines → infra → deployment.
- Rapidly experiment, iterate, and improve model performance with tight feedback loops.
- Collaborate with me on architecture decisions and product direction.
What I’m Looking For
- Strong experience fine‑tuning and deploying LLMs in production.
- Deep ML engineering skills: Python, PyTorch, transformers, distributed/accelerated training.
- Comfort handling messy, real‑world data and building robust pipelines.
- Ability to move quickly, make informed tradeoffs, and deliver production-quality systems.
- A builder’s mindset-resourceful, execution‑driven, and energized by 0→1 challenges.
⭐ Bonus Points
- Experience with agentic systems, tool‑calling, or structured reasoning workflows.
- Background in MLOps, model evaluation frameworks, or GPU-aware engineering.
- Early‑stage startup or founding-team experience.
Why Join
- Founding-level equity with meaningful ownership.
- Massive responsibility and autonomy over the AI systems at the heart of the product.
- Freedom to experiment, move fast, and push the boundaries of what LLMs can do.
San Francisco, CA (Hybrid/On‑site preferred)
Founding Team * Full‑Time
$250,000-$300,000 salary + equity
To Apply for this Job Click Here
Head of AI
San Francisco
$280000 - $320000
+ Data Science & AI
PermanentSan Francisco, California
To Apply for this Job Click Here
Head of AI – San Francisco, CA
Start-up‑Focused Role – $280,000-$320,000 + Equity
About the Role
A fast‑moving startup is seeking a Head of AI to build and lead its artificial intelligence function from the ground up. This is a high‑ownership role designed for someone who thrives in early‑stage environments, moves quickly, and is excited to shape both technical direction and company culture.
What You’ll Do
- Own the entire AI strategy and roadmap, guiding the evolution from early prototypes to scalable production systems.
- Design, train, fine‑tune, and deploy AI/ML models end‑to‑end, remaining hands‑on through early growth phases.
- Build and lead the AI organization – hiring, mentoring, and establishing team structure and best practices.
- Rapidly experiment and iterate, balancing scrappy execution with thoughtful long‑term architecture.
- Establish all AI infrastructure, including data pipelines, training workflows, model hosting, and MLOps foundations.
- Collaborate closely with founders and product/engineering teams to identify high‑impact AI opportunities.
- Implement responsible AI practices from day one, ensuring safety, reliability, robustness, and transparency.
- Evaluate and integrate emerging AI technologies, including LLMs, agentic systems, and multimodal architectures.
- Set standards for experimentation, evaluation, benchmarking, and deployment, optimizing for speed and quality.
What Makes You a Great Fit
- 7-10+ years in AI/ML with significant hands‑on experience building and deploying real systems.
- A track record of shipping AI products or infrastructure in a startup or small‑team environment.
- Deep understanding of LLMs, modern ML frameworks, retrieval systems, data engineering, and model evaluation.
- Ability to move fast while maintaining strong engineering discipline.
- Comfort operating in ambiguity and making high‑impact decisions without perfect information.
- Natural leadership instincts with the ability to both set vision and execute.
- Advanced degree in ML/CS or equivalent practical experience.
Bonus Experience
- Previous experience as a founding ML engineer or early technical leader.
- Direct experience training, fine‑tuning, or analyzing LLMs, multimodal models, or agents.
- Familiarity with lightweight startup‑friendly ML infrastructure (e.g., serverless inference, vector search, lean MLOps).
- Demonstrated ability to build quickly while maintaining high safety and reliability standards.
Location
San Francisco, CA – hybrid role; in‑person collaboration preferred during early team formation.
Head of AI – San Francisco, CA
Start-up‑Focused Role – $280,000-$320,000 + Equity
To Apply for this Job Click Here
Director of Decision Science
London
£120000 - £135000
+ Data Science & AI
PermanentLondon
To Apply for this Job Click Here
Director of Decision Science
West London. £120000 to £135000 plus up to 50 percent bonus and share options. Hybrid with three days per week in the office.
You will play a central role in shaping the modelling strategy for a fast‑growing embedded finance provider. This is a chance to take full ownership of the underwriting and acquisition modelling roadmap, lead two technical teams, and influence how advanced models power customer growth across multiple international markets.
The Company
They are a data driven embedded finance organisation using partner‑supplied data and advanced modelling to deliver personalised financial products to small and medium sized businesses. Operating across the UK, Europe, and North America, they continue to scale rapidly and are investing heavily in decision science. Their environment offers the autonomy to set standards while working with high quality data and impactful lending products.
The Role
* Lead the end‑to‑end development, validation, and monitoring of underwriting and acquisition models across multiple regions.
* Set modelling standards and define what good looks like for build quality, documentation, and governance.
* Guide the long term roadmap for how models support customer acquisition, pricing, and portfolio performance.
* Oversee the integration of MLOps and model deployment into the decision science function.
* Partner with product, engineering, and commercial teams to translate model outputs into real business decisions.
* Manage model development and acquisition analytics teams, ensuring technical excellence and clear development pathways.
Your Skills and Experience
* Strong hands on experience building predictive models in Python using approaches such as gradient boosting.
* Experience working with consumer or commercial risk modelling, decision science, or similar data heavy environments.
* Ability to take a commercially minded approach to acquisition, pricing, and performance.
* Confident managing full model lifecycles including design, testing, deployment, and monitoring.
* Effective leadership and stakeholder skills within technical and non technical environments.
* MLOps or R experience is beneficial but not essential.
What They Offer
* £120000 to £135000 base salary.
* Bonus up to 50 percent, typically 30 to 40 percent.
* Share options.
* Hybrid working with three days per week in the office.
* Clear progression opportunities within a scaling, international business.
How to Apply
To be considered for this Director of Decision Science role, please apply with your CV.
To Apply for this Job Click Here
Machine Learning Engineer – Remote
New York
$150 - $165
+ Data Science & AI
ContractNew York
To Apply for this Job Click Here
The Company
Our client is an innovative gaming company focused on creating high‑quality, immersive experiences powered by advanced technology. They combine strong engineering with creative design to develop games enjoyed by players worldwide, and are expanding their AI capabilities to push the boundaries of gameplay and simulation.
Role Overview
We are looking for an engineer who can take ownership of the full lifecycle of Reinforcement Learning (RL) systems-from model design and experimentation through large‑scale training and deployment. This position suits someone who enjoys working at the intersection of research, software engineering, and cloud computing, and who thrives in environments with complex data and evolving requirements.
What You’ll Do
- Develop RL solutions end‑to‑end, covering data pipelines, model design, training, and production deployment.
- Run RL and ML experiments using Python‑based machine learning frameworks.
- Implement, customize, and tune RL algorithms such as PPO, SAC, and DQN.
- Architect RL systems using modern cloud tools and distributed infrastructure.
- Improve RL training pipelines to maximize performance, scalability, and reliability.
Requirements (Must‑Have)
- Several years of experience delivering RL systems that have been used in real‑world or production environments.
- Deep understanding of core RL algorithm families and training workflows.
- Strong hands‑on experience with Python and frameworks like PyTorch or TensorFlow.
- Experience working with real RL datasets, including data formats, schemas, and collection processes.
- Proven ability to write production‑quality machine learning code.
Bonus Skills (Nice to Have)
- Experience with distributed RL frameworks (e.g., Ray RLlib).
- Familiarity with cloud platforms, with preference for experience on Google Cloud.
- Background in RL applied to computer vision.
- Exposure to backend engineering, DevOps, or MLOps infrastructure.
To Apply for this Job Click Here
Machine Learning Engineer (Reinforcement Learning)
Manhattan
$65 - $75
+ Data Science & AI
ContractManhattan, New York
To Apply for this Job Click Here
The Role:
You will design, train, optimize, and productionize Reinforcement Learning models at scale. This role is ideal for someone who is comfortable operating across research, engineering, and cloud systems while owning end‑to‑end RL development. You will work with complex datasets, ambiguous requirements, and modern distributed systems.
Key Responsibilities:
- Build RL solutions from data collection to deployment.
- Run ML and RL experiments using Python ML libraries.
- Implement and tune RL algorithms such as PPO, SAC, or DQN.
- Design RL architectures using cloud tooling.
- Optimize RL pipelines for speed, scale, and reliability.
Requirements (Must Have):
- Multiple years experience delivering production or real‑world RL solutions.
- Strong knowledge of RL algorithm families and training procedures.
- Hands‑on experience with Python, PyTorch or TensorFlow.
- Experience working with real RL datasets and associated data schemas.
- Experience shipping production‑ready ML code.
Nice to Have:
- Distributed RL (Ray RLLib).
- Cloud platforms (GCP preferred).
- CV‑based RL experience.
- Backend engineering or MLOps exposure.
To Apply for this Job Click Here
Vice President, Data Science
Atlanta
$300 - $400
+ Data Science & AI
PermanentAtlanta, Georgia
To Apply for this Job Click Here
VP of Data Science
Location: Atlanta, GA (in-office)
Onsite, 5x per week *please do not apply if you are not comfortable with this working arrangement
New opening for a VP of Data Science to lead and scale their in-house analytics capabilities. This is a high-impact role, driving advanced analytics, machine learning, and Generative AI across multiple portfolio brands to support smarter investment decisions and profitable growth.
The Role
-
Lead the Data Science function: team development, technical direction, model standards, and project delivery.
-
Define and execute the long-term vision for analytics, AI/ML, and GenAI across the organization.
-
Build predictive, scalable, and production-ready models that directly influence commercial and operational outcomes.
-
Partner with investment and portfolio teams to apply data science across consumer, retail, and multi-unit businesses.
-
Recruit, mentor, and grow a high-performing team of data scientists and analytics professionals.
What You’ll Bring
-
10+ years applying data science to business decision-making, with strong experience in Python, SQL, and cloud platforms (GCP preferred).
-
Proven ability to lead technical teams, manage multiple initiatives, and influence senior stakeholders.
-
Deep expertise in statistical modeling, machine learning, causal inference, experiment design, and analytics infrastructure.
-
Experience deploying repeatable models in production to deliver measurable business impact.
-
Strong communication and business acumen; able to translate complex analytics into actionable insights.
Desirable
-
MBA, Master’s, or PhD in a quantitative discipline.
-
Experience with multi-brand organizations or consulting frameworks.
-
Background in consumer, retail, or services sectors.
-
Hands-on experience with MLOps, model lifecycle management, and GenAI productivity tools.
Why This Role is Exciting
-
Lead enterprise-level analytics and AI across a diverse, high-performing portfolio.
-
Build and scale a world-class Data Science function from strategy to execution.
-
Work in a fast-paced, entrepreneurial environment with broad exposure to multiple brands and business challenges.
Eligibility: Must be authorized to work in the U.S. without sponsorship
To Apply for this Job Click Here
Director of Decision Science
London
£120000 - £150000
+ Risk Analytics
PermanentLondon
To Apply for this Job Click Here
Director of Decision Science
London, hybrid working (3 days in office)
£120,000 – £150,000
The Company
They are a data‑driven FinTech who are growing well. With continued global expansion, investment in analytics and their models is a key priority and this role would allow you to lead from the front and create impact across the business.
The Role
* Lead end to end development of underwriting and acquisition models.
* Set modelling standards, quality controls, and documentation practices.
* Oversee deployment with MLops
* Work closely with engineering, product, commercial, and data teams.
Your Skills and Experience
* Strong hands on experience building models in Python.
* Background in credit risk, rating agency modelling, or customer behaviour modelling.
* Confident communicator with senior stakeholders.
* Leadership experience in technical teams.
* Experience with XGBoost or other boosting techniques.
* Knowledge of MLOps or R is a plus but not essential.
What They Offer
* £120,000 to £150,000 base salary.
* Bonus
* Share options.
* Hybrid working, three days per week in a London office.
How to Apply
If you are interested in this opportunity, please submit your application
To Apply for this Job Click Here
MLOps Engineer
London
£90000 - £110000
+ Data Science & AI
PermanentLondon
To Apply for this Job Click Here
MLOps Engineer
London Based – Hybrid (Three days per week on site)
£90,000 to £110,000 plus bonus
This is an exciting opportunity to join a mission driven cleantech scale up as they continue to grow their data and AI function. You will help shape a modern MLOps environment, working on impactful machine learning deployments that directly support smarter, cleaner energy systems.
The Company
They are a fast growing technology scale up within the energy and electric space. The team is collaborative, customer focused, and driven by a strong product mindset. You would be joining a small, high impact data group with experienced engineers and the opportunity to take real ownership.
The Role
In this MLOps Engineer role, you will contribute to the design, deployment and optimisation of production ML systems.
Responsibilities include:
- Supporting data scientists and AI engineers to build, deploy and monitor ML models in production environments.
- Managing ML lifecycle
- Designing scalable ML pipelines for training, validation and deployment.
- Implementing CI/CD workflows for machine learning and maintaining reliable ML endpoints.
- Working heavily with AWS, including SageMaker, to deliver robust, secure and scalable ML infrastructure.
- Applying strong engineering standards across cloud, DevOps and automation practices.
- Contributing to computer vision and broader ML workloads, with scope to support new AI initiatives as they grow.
Your Skills and Experience
To succeed, you will bring strong commercial experience in:
- Python and applied ML engineering.
- MLOps tooling such as MLflow and modern experiment tracking platforms.
- Deploying models into production, including monitoring, testing and automation.
- AWS, with practical experience using SageMaker.
- Cloud and DevOps foundations including Docker and AWS
- Building scalable data and ML pipelines with solid engineering practices.
- You work well in fast paced environments, communicate clearly, and enjoy collaborating with cross functional teams.
What They Offer
- Competitive salary plus discretionary bonus.
- Hybrid working with three days each week in their London office.
- A high impact role within a growing data and AI team.
- Strong ownership, rapid development opportunities and exposure to modern ML tooling.
- A mission led environment focused on accelerating the transition to clean energy.
How To Apply
Please register your interest by sending your CV to Madison Barlow via the Apply link on this page.
To Apply for this Job Click Here
MLOps Engineer
London
£80000 - £90000
+ Data Science & AI
PermanentLondon
To Apply for this Job Click Here
MLOps Engineer
London Based – Hybrid (Three days per week on site)
£80,000 to £90,000 plus bonus
This is an exciting opportunity to join a mission driven cleantech scale up as they continue to grow their data and AI function. You will help shape a modern MLOps environment, working on impactful machine learning deployments that directly support smarter, cleaner energy systems.
The Company
They are a fast growing technology scale up within the energy and electric space. The team is collaborative, customer focused, and driven by a strong product mindset. You would be joining a small, high impact data group with experienced engineers and the opportunity to take real ownership.
The Role
In this MLOps Engineer role, you will contribute to the design, deployment and optimisation of production ML systems.
Responsibilities include:
- Supporting data scientists and AI engineers to build, deploy and monitor ML models in production environments.
- Managing ML lifecycle
- Designing scalable ML pipelines for training, validation and deployment.
- Implementing CI/CD workflows for machine learning and maintaining reliable ML endpoints.
- Working heavily with AWS, including SageMaker, to deliver robust, secure and scalable ML infrastructure.
- Applying strong engineering standards across cloud, DevOps and automation practices.
- Contributing to computer vision and broader ML workloads, with scope to support new AI initiatives as they grow.
Your Skills and Experience
To succeed, you will bring strong commercial experience in:
- Python and applied ML engineering.
- MLOps tooling such as MLflow and modern experiment tracking platforms.
- Deploying models into production, including monitoring, testing and automation.
- AWS, with practical experience using SageMaker.
- Cloud and DevOps foundations including Docker and AWS
- Building scalable data and ML pipelines with solid engineering practices.
- You work well in fast paced environments, communicate clearly, and enjoy collaborating with cross functional teams.
What They Offer
- Competitive salary plus discretionary bonus.
- Hybrid working with three days each week in their London office.
- A high impact role within a growing data and AI team.
- Strong ownership, rapid development opportunities and exposure to modern ML tooling.
- A mission led environment focused on accelerating the transition to clean energy.
HOW TO APPLY
Please register your interest by sending your CV to Madison Barlow via the Apply link on this page.
To Apply for this Job Click Here
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Industry Hub
HARNHAM
News & Blog
With over 10 years experience working solely in the Data & AI sector our consultants are able to offer detailed insights into the industry.
Visit our Blogs & News portal or check out our recent posts below.
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Frequently Asked Questions: Machine Learning Operations
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Candidate – Chief Data Officer
It was a real treat to work with Harnham. My recruiter consistently went above and beyond to ensure that I navigated through the recruitment process as smooth as possible. I had been in contact with other professional at Harnham in the past and I can attest that the level of professionalism is always top-notch.
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I have worked with Harnham for over 2 years now as our main Analytics Recruiter partner and I am very pleased with the overall service and the people we have hired via Harnham. Harnham’s team is very good at understanding our recruitment needs and always come back with relevant and well scanned CVs, which saves me precious time.
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Candidate – Senior Data Engineer
I've been a Senior Data Engineer for about 4-5 years and Harnham is one of the best recruitment agencies I worked with. There was a time when my offer fell through and the recruiter I was working with at Harnham jumped in to the rescue and scheduled interviews for me within a couple of days. Really good agency and some great people.
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Candidate – Data Analyst
I’ve had a great experience with Harnham. The recruiter provided great advice and ensured that I understood everything, and even followed up with me after I started my new role to see how I was settling in. I would recommend Harnham as a great recruitment company for anyone looking for a role in data and analytics.
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Client – Director of Customer Data Science – Apparel
The team at Harnham have been outstanding in helping our company build a market-leading data science team. Harnham’s communication is great, and the recruiter’s take a consultative approach that’s really focused on provided value for both their clients and their candidates. They provide strong candidates that help us fill our roles with high achievers who are also a great fit for our culture.
Client /
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Client – Director of People Operations
We’ve been collaborating with Harnham to recruit some key positions for our company, and they have been incredible partners. They team has been great and efficient. They understood our needs perfectly and provided us very talented candidates. We'll keep collaborating with them in the future. Thank you for your excellent job!
