Chicago 
EXECUTIVE DATA & ai RECRUITMENT

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Staff Machine Learning Scientist

Location: SF Bay Area – Hybrid (3 days/week onsite)

Salary: $200-260k base + Equity

A leading commerce marketplace with 130M+ users and billions of daily events is hiring a Staff Machine Learning Scientist to drive innovation across personalization, feed ranking, computer vision, and GenAI. You’ll work on high-impact ML solutions that directly shape user experience and business outcomes at massive scale.

What You’ll Do

• Lead full-lifecycle ML projects from idea to production across core areas like personalization, trust & safety, marketing optimization, and user engagement.
• Own the ML development process-from data exploration and feature engineering to model training, deployment, and post-launch optimization.
• Collaborate cross-functionally with ML engineers, PMs, and business stakeholders to identify and prioritize high-leverage initiatives.
• Experiment with emerging AI techniques, including GenAI, computer vision, and LLMs, to push the boundaries of what’s possible on the platform.
• Build scalable, production-ready ML systems that enhance key metrics like retention, engagement, and conversion.

What You Bring

• 7-10 years of experience building, deploying, and maintaining ML models at scale.
• Deep expertise in Python, SQL, Spark (PySpark or Scala) and frameworks like PyTorch or TensorFlow.
• Proven track record in consumer tech or large-scale marketplaces companies.
• Hands-on experience with CNNs, Transformers, Vision Transformers, and personalization algorithms.
• Background in user behavior modeling, search relevance, or real-time data systems.
• Strong foundation in experimentation (A/B testing), statistics, and applied ML.
• Exceptional communication skills and the ability to translate technical insights into business value.

• Experience with LLMs, RAG (Retrieval-Augmented Generation), or PEFT (Parameter-Efficient Fine-Tuning) techniques.

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Machine Learning Engineer

Location: New York (Hybrid)

Compensation: $180,000 – $220,000 base salary + Equity

About the Company

We’re partnered with a cutting-edge software company that’s redefining how development teams build, maintain, and scale modern applications. As engineering workflows grow increasingly complex, their intelligent platform empowers teams by deploying AI agents that automate repetitive development tasks, streamline workflows, and enhance productivity. These AI-driven systems are already transforming the software development lifecycle in dynamic environments-and the company is now scaling rapidly to meet market demand.

The Role

As an Applied AI/NLP Scientist, you’ll play a key role in designing and deploying advanced NLP and LLM-based solutions that accelerate and enhance software engineering workflows. Working directly with senior technical leadership, you’ll drive projects from early-stage research to production-ready implementations, with real impact on the development process.

Key Responsibilities

• AI Model Innovation: Architect and implement domain-specific LLM/NLP models tailored to the needs of software engineering use cases-code generation, documentation automation, code review assistance, and more.
• Research to Production: Lead end-to-end development of NLP/LLM solutions, from proof-of-concept to scalable production systems.
• Model Optimization: Improve model efficiency and output through fine-tuning, prompt engineering, RAG (retrieval-augmented generation), and inference techniques.
• Cross-Functional Collaboration: Work alongside product managers, developers, and leadership to ensure AI capabilities align with platform strategy and user needs.
• Thought Leadership: Help shape best practices around applied NLP/LLM development, contribute to internal innovation, and author papers or patents where applicable.
• Mentorship: Provide guidance and mentorship to junior ML researchers and engineers.

Your Skills and Experience

We’re looking for a hands-on NLP expert with a passion for building tools that empower developers:

• 2-8 years of experience in applied NLP or LLM-focused system development.
• Proven track record building and deploying NLP/LLM solutions in production.
• Proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, HuggingFace, spaCy).
• Experience working with large, unstructured code and text datasets.
• Background in applied research with an ability to bring experimental models into real-world systems.
• Deep understanding of transformer-based architectures, prompt tuning, fine-tuning, and retrieval-augmented methods.
• Strong communication skills and comfort working in fast-paced, ownership-driven environments.
• Advanced degree (PhD or Master’s) in Computer Science, AI, NLP, or a related field (PhD preferred).
• Bonus: Publications in top-tier AI/ML/NLP venues (e.g., NeurIPS, ACL, ICLR, EMNLP).

The Benefits

• Competitive Pay: $180,000 – $220,000 base + performance bonus + equity
• Innovation Ownership: Contribute directly to product innovation and IP
• Comprehensive Benefits: Health, dental, vision, 401(k), generous PTO, and more

How to Apply

To explore this opportunity, please submit your resume to Luc Simpson-Kent using the Apply link on this page.

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Principal Machine Learning Engineer – Recommendation & Relevancy

Location: New York (Hybrid – 4 days onsite)

Compensation: $600,000 – $1,500,000 total package

(Base Salary: $360,000-$400,000 + Equity + Exceptional Benefits)

THE COMPANY

Join a hyper-growth global e-commerce innovator that’s reshaping how businesses deliver real-time, personalized experiences at the point of purchase. Leveraging cutting-edge AI and ML at massive scale, this organization is building the future of intelligent commerce-and you could be a key part of it.

With explosive growth, a high-caliber team, and a tech-first culture, this is a unique opportunity to drive meaningful impact in a fast-paced, data-driven environment.

THE ROLE

As a Principal Machine Learning Engineer, you’ll drive the design and deployment of large-scale, intelligent decision-making systems. From personalized recommendations to smart bidding and real-time optimization, your work will directly influence millions of transactions and customer experiences daily.

You’ll collaborate closely with product and engineering partners to build ML solutions that are both cutting-edge and production-ready.

Key Focus Areas:

• Smart bidding and budget pacing algorithms
• Real-time recommendation engines
• Lookalike modeling and customer targeting
• CTR/CVR modeling and conversion optimization

Responsibilities:

• Architect and deploy end-to-end ML solutions at scale
• Develop robust data pipelines, feature stores, and orchestration frameworks
• Build high-performance, production-grade ML models (batch & real-time)
• Lead experimentation (offline & online), including A/B testing and model tuning
• Drive engineering excellence with well-tested, maintainable, scalable code
• Mentor team members and contribute to a culture of technical growth

YOUR SKILLS & EXPERIENCE

• PhD or Master’s degree in Machine Learning, Computer Science, or a related field
• 10+ years of hands-on experience building production ML systems at scale
• Expertise in AWS, TensorFlow, Feature Store technologies, and orchestration tools (e.g., Kubeflow, Airflow)
• Deep knowledge of at least two of the following:
• Bayesian methods
• Recommender systems
• Multi-task or meta-learning
• CTR/CVR prediction models

Bonus: Experience with advanced model architectures like Deep & Cross Network v2, Multi-gate Mixture-of-Experts, or Deep & Wide Networks.

BENEFITS

• Significant equity in a high-growth tech company
• Premium, fully covered health insurance (you + family)
• 401(k) with 4% dollar-for-dollar match
• Catered lunches and daily snacks
• Global travel opportunities
• Inclusive, collaborative culture with a strong focus on innovation, diversity, and impact

✅ HOW TO APPLY

Ready to solve real-world problems at scale and push the boundaries of applied machine learning? Apply now to speak with one of our specialist recruiters and learn more about this high-impact opportunity.

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Principal Machine Learning Engineer – Recommendation / Relevancy

Location: New York (Hybrid – 4 days onsite)

Compensation: Total package between $600,000 – $1,500,000

(Base salary: $360,000-$400,000 + Equity + Exceptional Benefits)

THE COMPANY

This hyper-growth, global e-commerce leader is transforming how businesses deliver personalized and relevant experiences at the point of purchase. With a strong focus on cutting-edge AI/ML technologies, this organization is scaling rapidly and looking to expand their world-class engineering team.

THE ROLE

As a Principal Machine Learning Engineer, you’ll play a critical role in shaping the next generation of intelligent decision-making systems. You’ll partner with product and engineering teams to build and productionize ML solutions that drive relevance and performance in real-time, at scale. Key focus areas include smart bidding, lookalike modeling, budget pacing, and personalized recommendations.

Key Responsibilities:

• Collaborate with cross-functional teams to define, architect, and deploy ML solutions to complex business problems.
• Design and build production-ready ML models, data processing pipelines, and robust deployment systems.
• Contribute to scalable codebases, with a strong emphasis on testing (unit, integration, performance).
• Explore and prototype state-of-the-art models, conducting both offline and online experiments.
• Share knowledge through tech talks, internal workshops, and mentorship.

YOUR SKILLS & EXPERIENCE

• PhD or Master’s in Machine Learning or a related field
• 10+ years of industry experience building end-to-end production ML systems
• Strong background in AWS, TensorFlow, Feature Store technologies, and orchestration tools (e.g., Kubeflow)
• Expertise in at least two of the following: Bayesian methods, recommender systems, multi-task learning, meta-learning, CTR or CVR modeling
• Bonus: Familiarity with architectures such as Deep & Cross Network v2, Multi-gate Mixture-of-Experts, Deep & Wide

BENEFITS

• Equity in a high-growth business
• Premium, fully covered health insurance for you and your family
• 401(k) with 4% dollar-for-dollar match
• Catered lunch and snacks daily
• Global travel opportunities
• Collaborative, inclusive culture with a strong focus on diversity and innovation

HOW TO APPLY

If you’re a senior-level ML engineer looking to make a real-world impact in a high-scale, high-growth environment, apply now to speak with one of our specialist recruiters.

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Machine Learning Engineer

Healthcare | Human Behaviour | Predictive ML

Washington, D.C. | Hybrid (Tues & Thurs in-office)

Up to $140,000 + Equity + Benefits

Are you passionate about applying machine learning to real-world healthcare challenges? Want to help decode why patients behave the way they do, and use that to improve health outcomes at scale?

Harnham is working with a mission-driven, human-centric AI company using cutting-edge behavioural data and predictive modelling to transform healthcare delivery. Their proprietary platform delivers deep insight into what drives patient decisions, and they’re looking for a Senior Data Scientist/MLE to lead the next evolution of this powerful asset.

THE ROLE

As a Senior Data Scientist/MLE, you’ll own the development of their flagship socio-behavioural data product – refining large-scale ML models, integrating new datasets (including geospatial data), and leading scientific validation. You’ll collaborate across Product, R&D, and Client teams to embed behavioural intelligence into pharma solutions that drive real-world impact.

This is a high-impact, strategic role in a fast-paced, purpose-led start-up environment.

YOUR RESPONSIBILITIES

• Lead the ML development and validation of a large-scale socio-behavioural data product
• Build and optimize hundreds of models using Python and Databricks
• Identify and integrate novel data sources to enrich behavioural insights
• Collaborate cross-functionally to bring insights into real-world pharma use cases
• Ensure fairness and scientific rigour in all models, especially across diverse populations

YOUR SKILLS

• 5+ years of experience building ML models using large healthcare or behavioural datasets
• Expert-level Python and strong Databricks proficiency
• Deep interest in behavioural science and its impact on health outcomes
• Strong technical voice with a hands-on approach to scalable data science
• Thrives in a collaborative, entrepreneurial setting

WHAT’S ON OFFER?

• Up to $140,000 base + Equity
• Unlimited PTO + 11 holidays
• 401k employer match
• Hybrid working: 2 days/week in D.C. office

If you are interested, Apply!

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Senior Staff Machine Learning Engineer – Recommendation Systems

Location: New York (Hybrid – 4 days onsite)

Compensation: Total package between $600,000 – $800,000

(Base salary: $315,000-$370,000 + Equity + Exceptional Benefits)

THE COMPANY

This hyper-growth, global e-commerce leader is transforming how businesses deliver personalized and relevant experiences at the point of purchase. With a strong focus on cutting-edge AI/ML technologies, this organization is scaling rapidly and looking to expand their world-class engineering team.

THE ROLE

As a Principal Machine Learning Engineer, you’ll play a critical role in shaping the next generation of intelligent decision-making systems. You’ll partner with product and engineering teams to build and productionize ML solutions that drive relevance and performance in real-time, at scale. Key focus areas include smart bidding, lookalike modeling, budget pacing, and personalized recommendations.

Key Responsibilities:

• Collaborate with cross-functional teams to define, architect, and deploy ML solutions to complex business problems.
• Design and build production-ready ML models, data processing pipelines, and robust deployment systems.
• Contribute to scalable codebases, with a strong emphasis on testing (unit, integration, performance).
• Explore and prototype state-of-the-art models, conducting both offline and online experiments.
• Share knowledge through tech talks, internal workshops, and mentorship.

YOUR SKILLS & EXPERIENCE

• PhD or Master’s in Machine Learning or a related field
• 10+ years of industry experience building end-to-end production ML systems
• Strong background in AWS, TensorFlow, Feature Store technologies, and orchestration tools (e.g., Kubeflow)
• Expertise in at least two of the following: Bayesian methods, recommender systems, multi-task learning, meta-learning, CTR or CVR modeling
• Bonus: Familiarity with architectures such as DCNv2, MMOE, Deep & Wide, or ESMM

BENEFITS

• Equity in a high-growth business
• Premium, fully covered health insurance for you and your family
• 401(k) with 4% dollar-for-dollar match
• Catered lunch and snacks daily
• Global travel opportunities
• Collaborative, inclusive culture with a strong focus on diversity and innovation

HOW TO APPLY

If you’re a senior-level ML engineer looking to make a real-world impact in a high-scale, high-growth environment, apply now to speak with one of our specialist recruiters.

To Apply for this Job Click Here

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Director/Senior Director, Data Science and Machine Learning

Location: San Francisco

Hybrid (2-3 days in office per week)

Salary: $250-300k base + bonus + equity

A growing digital healthcare technology company seeking a Data Science Leader to join our team. This player-coach role combines technical execution with strategic leadership, guiding high-impact AI and machine learning projects while mentoring a team of data scientists and data engineers.

You’ll work closely with Product Development, Customer Experience, and Solution Consulting to deliver actionable business and clinical insights for biotech and pharmaceutical companies.

Key Responsibilities

• Lead and mentor the Data Science team, ensuring high-quality delivery of advanced analytics and ML solutions.

• Drive the design of scalable Analytics Data Models and secure, production-level code.

• Guide research and productionalization of machine learning solutions to enhance the user experience of the platform

• Oversee Data Engineering functions to integrate structured and unstructured data into the data warehouse, delivering business intelligence reporting
• Ensure the data and engineering team produces production code at high quality within the architecture, emphasizing insights, compliance, and scalability

• Collaborate cross-functionally to enhance products and ensure operational excellence.

• Stay current on emerging technologies to drive innovation.

Who You Are

• 3+ years managing Data Science or Advanced Analytics teams.

• 7+ years in advanced biopharma analytics for Commercial or Market Access.

• Strong in Python, SQL, ML methodologies (e.g., regression, NLP, time series).

• Experienced with data modeling, ETL processes, and Snowflake environments.

• Effective communicator with strong prioritization and organizational skills.

• M.S. in Computer Science, Engineering, Data Science, or related field.

If you’re passionate about healthcare innovation and want to drive meaningful impact in a fast-paced environment, we’d love to hear from you.

To Apply for this Job Click Here

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Director of Machine Learning Engineering

AdTech | Remote – US Based | $220,000 – $260,000 + Bonus + Equity

Are you a hands-on leader who thrives at the intersection of machine learning systems, real-time infrastructure, and business impact?

We’re working with one of the fastest-growing AI-led AdTech platforms in the industry. Recently recognized for award-winning innovation in programmatic advertising, this company is redefining how brands apply custom AI to optimize media buying across major DSPs, Meta, and YouTube.

They’re now seeking a Director of Machine Learning Engineering to lead their end-to-end ML systems – from architecture to deployment – while mentoring a team of senior MLEs and collaborating closely with engineering and product.

If you’re passionate about building robust, scalable ML pipelines and shaping the future of real-time decisioning, this role is for you.

THE ROLE

As Director of Machine Learning Engineering, you’ll:

• Own the architecture, deployment, and performance of custom ML systems used for large-scale ad bidding and decisioning.

• Lead the design and optimization of low-latency pipelines built with Databricks, PySpark, Kubernetes, and Rust.

• Oversee LLM and neural network-based models, ensuring they are production-ready and aligned with business strategy.

• Collaborate with the Engineering Architect to build resilient, scalable ML infrastructure.

• Mentor and manage a growing team of 3+ MLEs, fostering high standards in ML software engineering.

• Guide adoption of emerging technologies like LoRA, quantization, vector stores, and Rust microservices for model serving.

• Partner cross-functionally to translate business objectives into impactful AI solutions.

SKILLS & EXPERIENCE

To be successful, you will need:

• 8+ years of experience in machine learning engineering, with 3+ years in leadership roles.

• Deep expertise in building real-time ML systems with Kubernetes, Rust, PySpark, Databricks, and deep learning frameworks like PyTorch or TensorFlow.

• A proven track record of deploying LLMs and neural networks at scale.

• Mastery of MLOps tools including MLflow, Prometheus, Grafana, Airflow, etc.

• Strong cloud and data engineering experience (especially AWS and Databricks).

• A hands-on mindset with the ability to influence technical architecture and direction.

• Exceptional collaboration and communication skills across engineering and executive stakeholders.

• Experience in AdTech or performance marketing is a strong advantage.

BENEFITS

• Highly competitive base + performance bonuses + equity

• Unlimited PTO, 11 company holidays, and year-end closure

• Full medical, dental, vision & 401k options

• Fully remote role within the US

• Opportunity to shape a best-in-class AI platform used by global brands

• Work in a transparent, high-ownership culture that values innovation and technical excellence

Interested in leading at the cutting edge of ML infrastructure in AdTech?

Apply now to connect with a consultant at Harnham.

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Director of Machine Learning
NYC

An award-winning AI company at the forefront of real-time programmatic technology, delivering impactful, data-driven solutions for global brands.

Mission:

We’re looking for a Senior Machine Learning Engineering Leader to own the ML infrastructure and guide the technical strategy. You will lead a team of engineers, ensure scalable, fault-tolerant ML pipelines, and collaborate with product and engineering teams to align ML systems with business goals.

Desired Profile:

• Minimum 8 years in ML engineering, with at least 3 years in leadership roles.

• Hands-on experience with cloud platforms (AWS, Databricks), MLOps tools (MLflow, Prometheus), and CI/CD pipelines.

• Proficiency with deploying low-latency ML solutions and advanced architectures, including LLMs, vector stores, and Rust microservices.

• Strong stakeholder communication and ability to mentor and grow engineering talent.

• Background in advertising or performance marketing a bonus.

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Staff Machine Learning Engineer – NLP & LLMs

Location: Fully Remote
Compensation: $250,000 – $275,000 base salary + bonus + benefits

ABOUT THE COMPANY

We are partnered with a market leader in the legal and financial services industry, driving innovation through AI. This company is revolutionizing how professionals interact with data by integrating cutting-edge NLP and LLM technologies. As their platform scales, they are seeking a highly skilled Machine Learning Engineer to take the lead in developing, deploying, and optimizing advanced AI models that directly impact high-value, high-regulation environments.

This is an opportunity to build mission-critical systems from the ground up and work alongside some of the top minds in AI and law.

THE ROLE

As a Staff Machine Learning Engineer, you will work closely with researchers and the C-suite to design and implement robust machine learning infrastructure and end-to-end NLP/LLM pipelines. You will bridge the gap between experimentation and scalable deployment, contributing to the full lifecycle of AI products.

Your Responsibilities Will Include:

• Model Deployment & Scaling: Engineer and deploy large-scale NLP and LLM models for production environments.

• Infrastructure & Tooling: Build and maintain data pipelines, training workflows, and inference systems optimized for low-latency and high-accuracy.

• End-to-End Development: Take PoCs from research stage to production-grade systems, focusing on performance, reliability, and maintainability.

• Optimization: Improve existing model architectures and fine-tune LLMs using retrieval-augmented generation (RAG), prompt tuning, quantization, and efficient inference techniques.

• Collaboration: Partner with Applied Scientists, Legal SMEs, and Product Leaders to align technical solutions with business and user needs.

• Code Quality: Write clean, scalable, and well-documented code using industry best practices.

YOUR SKILLS AND EXPERIENCE

We are looking for an experienced and versatile Staff Machine Learning Engineer with the following qualifications:

• 5+ years of experience deploying NLP and ML models in production environments.

• Strong software engineering background in Python, with experience using frameworks like TensorFlow, PyTorch, spaCy, Hugging Face Transformers, and more.

• Demonstrated ability to scale models and build distributed training/inference systems.

• Experience working with large datasets and knowledge of data pipelines, MLOps tools (e.g., MLflow, Kubeflow, Airflow), and cloud infrastructure (AWS, GCP, or Azure).

• Deep understanding of NLP concepts and LLM architectures (BERT, GPT, T5, etc.).

• Comfortable working cross-functionally with researchers, product teams, and senior leadership.

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field (PhD a plus, but not required).

• Bonus: Contributions to open-source NLP projects or publications in applied ML conferences (NeurIPS, ACL, EMNLP, etc.)

BENEFITS

• Top-Tier Compensation: Base salary of $250,000 – $275,000 + annual bonus.

• Fully Remote: Work from anywhere in the United States.

• Ownership: End-to-end responsibility for the models and systems you help build.

• Health & Retirement: Comprehensive medical, dental, vision, and 401(k) plans.

• Research-Driven Culture: Collaborate with world-class researchers and engineers solving impactful real-world problems.

HOW TO APPLY

Interested applicants should submit their resume to Tim Jonas via the Apply link on this page. We look forward to seeing how your engineering skills can help shape the future of legal and financial AI systems.

KEYWORDS:
Machine Learning | ML Engineering | NLP | LLMs | Deep Learning | Large Language Models | MLOps | Python | PyTorch | Hugging Face | TensorFlow | Cloud Infrastructure | Distributed Systems | RAG | Prompt Engineering | AI Platforms | Legal Tech | Financial Services | Applied ML | Model Deployment

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Staff Machine Learning Engineer

$220,000 – $260,000 (Base + Bonus)
Remote (NYC preferred, hybrid available)

About the Company

Imagine a future where AI doesn’t just assist in marketing-it drives it. That’s what we’re building.

Our client is leading the transformation of AI-powered marketing, helping global brands optimize ad spend, automate decision-making, and scale effortlessly. Backed by a world-class ML and Data Science team, we’re evolving beyond a traditional agency into a full-stack AI powerhouse, delivering cutting-edge solutions in LLMs, Diffusion Models, and predictive analytics.

If you want to work on AI that makes a measurable impact-think billions in ad spend optimized in real time-this is where you want to be.

The Role

We’re looking for a Staff Machine Learning Engineer to build, fine-tune, and deploy AI models at scale. You’ll be working with LLMs, Diffusion Models, and advanced predictive analytics to optimize ad performance, automate campaigns, and solve complex problems in marketing AI.

This is a hands-on role where you’ll collaborate with top engineers, data scientists, and product leaders to ship real AI solutions-fast.

What You’ll Do

• Develop and fine-tune LLMs, Diffusion Models, and predictive ML models to optimize ad performance.
• Design and deploy scalable AI solutions that automate campaign creation, optimization, and decision-making.
• Collaborate cross-functionally to integrate AI-driven automation into marketing systems.
• Work in a high-impact, fast-moving environment where your models go live and deliver real results.
• Solve complex challenges at the intersection of AI, advertising, and automation.

What You Bring

• Proven experience in ML/Data Science-no strict degree requirements, just real-world expertise.
• Strong experience with Python, TensorFlow, PyTorch, and model deployment.
• Background in LLM fine-tuning, diffusion models, and predictive analytics.
• Experience shipping ML products at scale-bonus points if you’ve done it at a FAANG or top AI-driven company.
• Preference for NYC-based candidates (4 days/week in office), but remote-friendly for the right fit.

The Perks

• Unlimited vacation
• Monthly telephone stipend
• Comprehensive medical, dental, and vision insurance
• 401(k) with matching
• Hybrid work option (NYC preferred)
• Professional development stipend
• Seamless meal allowance

How to Apply

Ready to build AI that transforms marketing? Send your resume to Cassie Wandell via the Apply link on this page.

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