DATA & ai RECRUITMENT in Charlotte NC

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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

$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

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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

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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

To Apply for this Job Click Here

Director of Machine Learning – NLP & LLMs

Location: Fully Remote
Compensation: $300,000 – $325,000 base salary + performance bonus + equity

ABOUT THE COMPANY

We are partnered with a high-growth company at the intersection of AI, legal tech, and financial services, fundamentally transforming how regulated industries leverage language models and machine learning. This organization is building sophisticated NLP/LLM systems to streamline complex workflows for legal and financial professionals.

With executive-level support and increasing product demand, they’re seeking a Director of Machine Learning to lead strategy, research, and engineering execution across NLP and LLM initiatives. This is a rare opportunity to drive technical vision, shape an elite ML team, and build impactful AI systems from the ground up in a regulated space.

THE ROLE

As Director of Machine Learning, you’ll be responsible for setting the long-term machine learning roadmap, leading technical teams, and ensuring the successful development and deployment of scalable NLP solutions. You will report directly to the Head of AI and work closely with executive leadership, product, and engineering.

Key Responsibilities:

• Strategic Leadership: Define the ML vision and roadmap for NLP and LLM-based solutions, aligned with company goals and customer needs.

• Team Building & Management: Hire, mentor, and manage a team of ML engineers and applied scientists. Foster a high-performing, collaborative environment.

• Technical Oversight: Guide end-to-end model development-from research and prototyping through production deployment, performance monitoring, and continuous optimization.

• Cross-Functional Influence: Collaborate with product, legal, engineering, and design teams to translate business needs into scalable AI solutions.

• Innovation: Stay ahead of the curve in LLM research and NLP advancements. Evaluate and implement new technologies and tools to maintain technical edge.

• Thought Leadership: Represent the company in industry discussions, conferences, and partner conversations. Champion best practices in ethical and responsible AI.

• Operational Excellence: Ensure strong MLOps foundations are in place, including CI/CD, data governance, model monitoring, and security practices.

YOUR SKILLS AND EXPERIENCE

Required Qualifications:

• 10+ years of experience in machine learning and software engineering, with at least 4+ years in a leadership or managerial role.

• Demonstrated success building and leading teams that develop and deploy NLP/LLM models at scale.

• Deep expertise in Python, ML frameworks (e.g., PyTorch, TensorFlow), and modern NLP tools (e.g., Hugging Face Transformers, spaCy).

• Experience designing and implementing ML systems in production, especially with large language models (e.g., GPT, BERT, T5).

• Proven ability to align technical initiatives with business goals, working cross-functionally with product and exec teams.

• Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and scalable ML pipelines.

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field; PhD preferred.

• Publication or open-source contributions in NLP/ML domains (e.g., ACL, NeurIPS, ICLR, EMNLP) a plus.

THE BENEFITS

• Executive-Level Compensation: $300,000 – $325,000 base + bonus + equity potential.

• Remote-First Culture: Work from anywhere in the United States or Canada.

• Elite Talent Environment: Collaborate with top-tier researchers, engineers, and domain experts.

• Comprehensive Benefits: Full health, dental, vision, 401(k), and wellness programs.

• Strategic Impact: Lead a core function at the center of the company’s long-term success.

HOW TO APPLY

Submit your resume to Tim Jonas via the Apply link on this page. We’re excited to connect with experienced ML leaders ready to guide cutting-edge AI development in a deeply impactful space.

KEYWORDS:
Director | Machine Learning | NLP | LLMs | AI Leadership | ML Strategy | Deep Learning | Natural Language Processing | AI Platforms | MLOps | Legal Tech | Financial Services | Model Deployment | Engineering Management | AI Infrastructure | Hugging Face | Generative AI | Enterprise AI

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Senior Machine Learning Engineer – NLP & LLMs (Mid-Level)

Location: Fully Remote

Compensation: $180,000 – $210,000 base salary + bonus + benefits

ABOUT THE COMPANY

We’re working with a cutting-edge financial services company transforming the legal space through advanced AI. Their mission: to make legal and financial workflows smarter, faster, and more cost-effective by leveraging the latest in natural language processing and machine learning. As they continue to expand their AI capabilities, they’re seeking a Machine Learning Engineer (Mid-Level) to join their growing NLP/LLM team.

This is a great opportunity for someone with solid production-level ML experience who wants to take the next step-working closely with seasoned researchers, engineers, and product leaders to build next-generation AI systems in a high-impact domain.

THE ROLE

As a Machine Learning Engineer, you’ll contribute to the development, deployment, and optimization of NLP models and AI infrastructure. You’ll be responsible for translating cutting-edge research into scalable, production-ready systems and collaborating with teams across engineering, research, and product.

Key Responsibilities:

• Model Development & Integration: Work with senior engineers and researchers to develop and integrate LLMs and NLP models into customer-facing products.
• Production-Ready Code: Build and maintain model pipelines that are scalable, testable, and efficient.
• Data Engineering: Help design and manage data pipelines, labeling workflows, and model training datasets.
• Model Tuning & Evaluation: Assist in prompt engineering, fine-tuning, evaluation, and benchmarking of NLP models.
• Collaboration: Partner with applied scientists and product teams to deliver end-to-end features powered by machine learning.
• Learning & Growth: Expand your skills through mentorship and exposure to cutting-edge NLP/LLM work and tooling.

YOUR SKILLS AND EXPERIENCE

We’re looking for a motivated engineer with a strong foundation in machine learning and an eagerness to grow within a fast-moving team.

Required Qualifications:

• 3-5 years of professional experience building and deploying ML models (with at least 2 years focused on NLP).
• Proficient in Python and familiar with ML libraries like TensorFlow, PyTorch, spaCy, or Hugging Face Transformers.
• Experience with model training, evaluation, and deployment in cloud environments (e.g., AWS, GCP, or Azure).
• Comfortable working with large datasets, data preprocessing, and version control tools (e.g., Git, DVC).
• Knowledge of modern NLP concepts and language model architectures (e.g., BERT, GPT, T5).
• Bachelor’s degree in Computer Science, Engineering, or a related field (Master’s a plus).

Bonus Points For:

• Experience with MLOps tools (e.g., MLflow, Airflow, Kubernetes).
• Previous work with legal, financial, or highly regulated data.
• Contributions to open-source NLP tools or public research.

BENEFITS

• Competitive Compensation: $180,000 – $210,000 base + bonus.
• Flexible & Remote: Work from anywhere in the United States or Canada.
• Health & Wellness: Comprehensive medical, dental, vision, and 401(k).
• Professional Growth: Work alongside experienced engineers and researchers in a high-learning environment.
• Impact: Contribute to real-world AI products used by professionals in law and finance.

HOW TO APPLY

Send your resume to Tim Jonas via the Apply link on this page. We’re excited to meet engineers who want to build meaningful, AI-driven systems in a space that matters.

KEYWORDS:

Machine Learning | NLP | LLM | Deep Learning | Generative AI | Model Deployment | Python | PyTorch | TensorFlow | Hugging Face | Prompt Engineering | ML Pipelines | Legal Tech | Financial Services | AI Infrastructure | Mid-Level Engineer | Scalable AI Systems

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