Chicago 
EXECUTIVE DATA & ai RECRUITMENT

To Apply for this Job Click Here

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.

To Apply for this Job Click Here

To Apply for this Job Click Here

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.

To Apply for this Job Click Here

To Apply for this Job Click Here

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

To Apply for this Job Click Here

To Apply for this Job Click Here

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.

To Apply for this Job Click Here

To Apply for this Job Click Here

Machine Learning Engineer

AI & Cloud Optimization

New York City – Hybrid

$180,000 – $220,000 + Equity & Benefits

We are working with a venture-backed AI startup redefining how companies manage their cloud costs in an era of explosive AI-driven growth. With billions spent annually on cloud infrastructure-often tracked with outdated tools-this company is building intelligent systems that bring clarity, automation, and financial control to cloud spend. Their platform is already trusted by industry leaders and built for scale across AWS, GCP, and Azure.

The Role:

This is a hands-on, senior-level position where you’ll drive AI product development from 0 to 1. As a Machine Learning Engineer, you’ll partner closely with the CTO and founding team to design and implement LLM-powered features, forecasting models, and intelligent automation capabilities that directly impact customer outcomes.

Responsibilities include:

• Designing, deploying, and optimizing machine learning models for cloud spend forecasting, anomaly detection, and cost control
• Building and integrating LLMs to power Agent-style chat interfaces and automation tools
• Developing secure, scalable ML infrastructure across multiple cloud platforms
• Driving full-cycle ML projects-architecture, development, deployment, monitoring, and iteration
• Collaborating with product, engineering, and leadership teams to align AI development with business priorities
• Experimenting with new techniques in generative AI, model optimization, and real-time inference

Requirements:

We’re looking for a startup-minded ML engineer with strong technical depth and a bias toward action. You should have:

• 5+ years of experience in machine learning, AI model development, and infrastructure deployment
• Fluency in Python, with experience in tools like PyTorch, Hugging Face, LangChain, and Terraform
• A proven ability to deploy ML models at scale across distributed cloud systems
• Experience working with LLMs and open-source models (e.g., Llama, Mistral, Falcon)
• An understanding of AI security best practices and a commitment to building responsibly
• Strong communication skills and the ability to convey complex ideas clearly and confidently
• Comfort in high-ambiguity, fast-paced environments where you’ll help define the roadmap

Benefits:

As a Machine Learning Engineer, you can expect:

$180,000 – $220,000 base salary

Equity in a high-growth company

Unlimited PTO and flexible work policy

To Apply for this Job Click Here

To Apply for this Job Click Here

Senior Lead Machine Learning Engineer – LLM Focus

Location: Minneapolis

Salary: $150,000 – $180,000 base + 20% Bonus

Company Overview:

Join a fast-growing, innovative organization at the forefront of artificial intelligence, committed to pushing boundaries in generative AI and Large Language Models (LLMs). We’re solving cutting-edge problems with scalable machine learning and deploying solutions across industries, from finance to healthcare to enterprise automation.

Role Overview:

We are seeking a Machine Learning Engineering Manager with deep expertise in LLMs and production-grade ML systems. This is a hands-on leadership role where you’ll oversee a team of up to 10 Machine Learning Engineers, while also contributing technically to high-impact AI solutions.

You’ll shape the roadmap for LLM initiatives, drive team performance, ensure technical excellence, and align engineering efforts with business objectives. This role combines engineering leadership, cross-functional collaboration, and strategic execution in a fast-paced environment.

Key Responsibilities:

• Lead and manage a team of up to 10 Machine Learning Engineers, providing mentorship, performance reviews, and career development guidance.
• Define and drive the engineering roadmap for LLM-based solutions and scalable ML systems.
• Collaborate with research, product, and data teams to align technical execution with strategic business needs.
• Guide development of ML/LLM solutions for tasks like summarization, classification, Q&A, and retrieval-augmented generation (RAG).
• Oversee implementation and optimization of transformer models (e.g., GPT, LLaMA, Claude, Mistral).
• Ensure best practices in model training, fine-tuning, evaluation, and deployment.
• Build robust ML pipelines with MLFlow, Airflow, or Kubeflow.
• Manage production deployments using Docker, Kubernetes, and serving frameworks (e.g., TensorFlow Serving, TorchServe, FastAPI).
• Lead efforts in CI/CD, monitoring, versioning, and model drift mitigation.
• Promote a high-performing, collaborative team culture and drive continuous learning and innovation.

Required Qualifications:

• MSc or PhD in Computer Science, Machine Learning, Engineering, or a related STEM discipline.
• 2+ years of experience managing and mentoring ML Engineers or cross-functional ML teams.
• Proven expertise in LLMs and transformer-based architectures (e.g., GPT, BERT, RoBERTa, T5).
• Strong production experience with ML/AI model development, deployment, and lifecycle management.
• Advanced Python skills and familiarity with libraries such as PyTorch, TensorFlow, Hugging Face Transformers.
• Proficiency with cloud platforms (AWS preferred), Kubernetes, and distributed systems (e.g., Spark, Kafka).
• Solid understanding of DevOps practices and CI/CD pipelines for machine learning.
• Exceptional communication and leadership skills; able to bridge technical and business discussions effectively.

Preferred Experience:

• Experience building and scaling retrieval-augmented generation (RAG) pipelines.
• Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and frameworks like LangChain or LlamaIndex.
• Knowledge of RLHF, prompt engineering, and generative model evaluation.
• Experience in regulated or high-security environments is a strong plus.

Compensation and Benefits:

• Base Salary: $150,000 – $180,000
• 20% Annual Bonus
• Flexible hybrid work setup
• Comprehensive benefits package (health, dental, vision)
• Annual learning & development budget, including AI/ML conference attendance

How to Apply:

To express your interest in this opportunity, please submit your CV via the “Apply” link on this page. We look forward to connecting with you!

To Apply for this Job Click Here

To Apply for this Job Click Here

Senior Lead Machine Learning Engineer – LLM Focus

Location: Toronto

Salary: $150,000 – $180,000 base + 20% Bonus

Company Overview:

Join a fast-growing, innovative organization at the forefront of artificial intelligence, committed to pushing boundaries in generative AI and Large Language Models (LLMs). We’re solving cutting-edge problems with scalable machine learning and deploying solutions across industries, from finance to healthcare to enterprise automation.

Role Overview:

We are seeking a Machine Learning Engineering Manager with deep expertise in LLMs and production-grade ML systems. This is a hands-on leadership role where you’ll oversee a team of up to 10 Machine Learning Engineers, while also contributing technically to high-impact AI solutions.

You’ll shape the roadmap for LLM initiatives, drive team performance, ensure technical excellence, and align engineering efforts with business objectives. This role combines engineering leadership, cross-functional collaboration, and strategic execution in a fast-paced environment.

Key Responsibilities:

• Lead and manage a team of up to 10 Machine Learning Engineers, providing mentorship, performance reviews, and career development guidance.
• Define and drive the engineering roadmap for LLM-based solutions and scalable ML systems.
• Collaborate with research, product, and data teams to align technical execution with strategic business needs.
• Guide development of ML/LLM solutions for tasks like summarization, classification, Q&A, and retrieval-augmented generation (RAG).
• Oversee implementation and optimization of transformer models (e.g., GPT, LLaMA, Claude, Mistral).
• Ensure best practices in model training, fine-tuning, evaluation, and deployment.
• Build robust ML pipelines with MLFlow, Airflow, or Kubeflow.
• Manage production deployments using Docker, Kubernetes, and serving frameworks (e.g., TensorFlow Serving, TorchServe, FastAPI).
• Lead efforts in CI/CD, monitoring, versioning, and model drift mitigation.
• Promote a high-performing, collaborative team culture and drive continuous learning and innovation.

Required Qualifications:

• MSc or PhD in Computer Science, Machine Learning, Engineering, or a related STEM discipline.
• 2+ years of experience managing and mentoring ML Engineers or cross-functional ML teams.
• Proven expertise in LLMs and transformer-based architectures (e.g., GPT, BERT, RoBERTa, T5).
• Strong production experience with ML/AI model development, deployment, and lifecycle management.
• Advanced Python skills and familiarity with libraries such as PyTorch, TensorFlow, Hugging Face Transformers.
• Proficiency with cloud platforms (AWS preferred), Kubernetes, and distributed systems (e.g., Spark, Kafka).
• Solid understanding of DevOps practices and CI/CD pipelines for machine learning.
• Exceptional communication and leadership skills; able to bridge technical and business discussions effectively.

Preferred Experience:

• Experience building and scaling retrieval-augmented generation (RAG) pipelines.
• Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and frameworks like LangChain or LlamaIndex.
• Knowledge of RLHF, prompt engineering, and generative model evaluation.
• Experience in regulated or high-security environments is a strong plus.

Compensation and Benefits:

• Base Salary: $150,000 – $180,000
• 20% Annual Bonus
• Flexible hybrid work setup
• Comprehensive benefits package (health, dental, vision)
• Annual learning & development budget, including AI/ML conference attendance

How to Apply:

To express your interest in this opportunity, please submit your CV via the “Apply” link on this page. We look forward to connecting with you!

To Apply for this Job Click Here