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Senior Machine Learning Engineer

Location: Remote (with optional hybrid New York)
Salary: Salary up to $220,000

THE COMPANY
Our client is a fast-growing, profitable technology business operating at the cutting edge of AI-driven decisioning. They partner with global brands to deliver advanced machine learning solutions that optimize real-time strategies across digital platforms.

THE ROLE
As a Senior Machine Learning Engineer, you will play a key role in building scalable ML infrastructure and deploying production-grade models that directly impact business outcomes. This is an opportunity to work on distributed systems, cutting-edge neural network architectures, and MLOps best practices in a high-performance environment.

RESPONSIBILITIES

• You will architect and train neural network models for optimization and audience modeling using PyTorch and distributed training frameworks.
• You will build multi-GPU training pipelines and implement hyperparameter tuning strategies.
• You will develop feature engineering workflows using PySpark and embedding techniques.
• You will own the ML lifecycle from training to batch inference, ensuring automation and reproducibility.
• You will implement monitoring and observability solutions to track model performance and system health.
• Collaborate with cross-functional teams to align ML initiatives with product strategy and KPIs.

REQUIREMENTS

• MSc or PhD in Computer Science, Machine Learning, or related field.
• Strong ML engineering with strong proficiency in PyTorch.
• Hands-on experience with Databricks.
• Expert-level Python and PySpark skills for large-scale data processing.
• Familiarity with cloud platforms (AWS) and data warehousing (Snowflake).
• Strong understanding of CI/CD workflows and best practices.

BENEFITS

• Competitive salary and bonus structure.
• Comprehensive health coverage.
• Generous PTO and company holidays.
• Flexible remote working options.

HOW TO APPLY
If you’re passionate about building scalable ML systems and want to work in a dynamic, innovative environment, apply today to learn more.

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Senior Machine Learning Engineer

Location: Remote (with optional hybrid New York)

Salary: Salary up to $220,000

THE COMPANY

Our client is a fast-growing, profitable technology business operating at the cutting edge of AI-driven decisioning. They partner with global brands to deliver advanced machine learning solutions that optimize real-time strategies across digital platforms.

THE ROLE

As a Senior Machine Learning Engineer, you will play a key role in building scalable ML infrastructure and deploying production-grade models that directly impact business outcomes. This is an opportunity to work on distributed systems, cutting-edge neural network architectures, and MLOps best practices in a high-performance environment.

RESPONSIBILITIES

• You will architect and train neural network models for optimization and audience modeling using PyTorch and distributed training frameworks.
• You will build multi-GPU training pipelines and implement hyperparameter tuning strategies.
• You will develop feature engineering workflows using PySpark and embedding techniques.
• You will own the ML lifecycle from training to batch inference, ensuring automation and reproducibility.
• You will implement monitoring and observability solutions to track model performance and system health.
• Collaborate with cross-functional teams to align ML initiatives with product strategy and KPIs.

REQUIREMENTS

• MSc or PhD in Computer Science, Machine Learning, or related field.
• Strong ML engineering with strong proficiency in PyTorch.
• Hands-on experience with Databricks.
• Expert-level Python and PySpark skills for large-scale data processing.
• Familiarity with cloud platforms (AWS) and data warehousing (Snowflake).
• Strong understanding of CI/CD workflows and best practices.

BENEFITS

• Competitive salary and bonus structure.
• Comprehensive health coverage.
• Generous PTO and company holidays.
• Flexible remote working options.

HOW TO APPLY

If you’re passionate about building scalable ML systems and want to work in a dynamic, innovative environment, apply today to learn more.

Desired Skills and Experience

MLOps, DataBricks

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Senior ML Engineer
Full Remote
$180K-$200K base

A fast-growing AI product company operating in real-time decisioning, large-scale machine learning, and data-driven optimization. The business builds advanced AI systems used by major brands to automate and optimize high-impact decisions at massive scale. Strong engineering culture, modern ML infrastructure, and real product ownership in a highly technical environment.

Mission

• Architect, train, and maintain distributed machine learning systems powering core AI products
• Build and optimize neural network models for large-scale prediction, classification, and optimization
• Develop feature engineering pipelines on big data using Spark and modern data platforms
• Own the full ML lifecycle: training, tuning, evaluation, batch inference, and observability
• Design and operate production-grade ML pipelines with a focus on reliability, automation, and reproducibility

Profile:

• 5-10 years of industry experience building and deploying ML systems at scale
• Hands-on experience with distributed training and large-scale data processing (e.g., Ray, Spark, multi-GPU)
• Deep understanding of MLOps best practices: model versioning, experiment tracking, monitoring, reproducibility
• Familiarity with cloud platforms (AWS or equivalent), modern data stacks, and CI/CD pipelines
• Bonus: experience in adtech, optimization systems, reinforcement learning, LLMs, or large-scale embeddings

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Principal Data Scientist
Full Remote (From the US)
Salary up to $210K base + bonus

A large, global technology-led organisation operating in a mission-driven, data-intensive domain. The business designs and scales complex digital platforms used by millions of end users worldwide, combining advanced data science, AI, and product engineering to drive measurable real-world impact.

Mission

• Act as technical lead for high-impact Data Science and AI initiatives across the organisation
• Define architectures, methodologies, and best practices for complex DS/AI and GenAI problem spaces
• Lead the design and delivery of production-grade AI systems, with particular focus on LLMs and generative AI
• Drive strategic initiatives by aligning DS/AI priorities with business and product objectives
• Mentor senior and junior data scientists, setting technical direction and raising engineering standards
• Own multiple projects simultaneously: scoping, prioritisation, delivery timelines, and stakeholder alignment

Profile

• PhD or equivalent in Data Science, Applied Mathematics, Statistics, or related field
• Senior-level experience: typically 6-10+ years in DS/AI roles, including leadership at Principal / Staff level
• Demonstrated technical leadership: defining strategy, owning complex initiatives, and mentoring teams
• Deep hands-on experience with production-scale DS/AI systems, with a strong recent focus on Generative AI / LLMs
• Expertise in LLM architectures, orchestration frameworks, and AI governance (guarding, scaling, monitoring, reliability)
• Strong understanding of MLOps / LLMOps in enterprise environments

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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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Forward Deployed Senior Data Scientist

Salary: $175,000+ (Depending on Experience)

Locations: Remote (with 25% travel)

THE COMPANY

A high‑growth, mission‑focused technology organisation is expanding its advanced analytics and AI function. Operating in a complex, data‑rich environment, the team builds scalable, high‑impact AI systems that support critical decision‑making and deliver tangible operational value. The environment is fast‑paced, innovative, and ideally suited to someone who thrives in high‑autonomy, high‑impact roles.

THE ROLE

As a Forward Deployed Senior Data Scientist, you will work directly with stakeholders to translate complex problems into deployable AI solutions. You’ll use a combination of proprietary and commercial datasets to uncover insights, build models, and deploy production‑ready systems that support strategic decision‑making.

This role blends hands‑on data science, AI engineering, rapid prototyping, and end‑to‑end delivery ideal for someone who is highly analytical, scrappy, and passionate about solving complex technical challenges with real‑world impact.

KEY RESPONSIBILITIES

• Build advanced AI/ML/DS models and systems tailored to high‑value operational challenges
• Develop new AI‑driven technology stacks designed for specific customer use cases
• Lead end‑to‑end delivery of AI projects, from scoping to production deployment
• Partner with research, engineering, and software teams to deliver robust AI products
• Define architectural standards and project roadmaps for scalable AI systems
• Create evaluation frameworks for AI deployments, including performance, reliability, and observability
• Mentor junior team members and help shape a culture of excellence and innovation
• Stay current with emerging techniques in AI, LLMs, and agentic systems; drive adoption of best practices
• Build agentic AI systems leveraging reasoning frameworks and orchestrators
• Act as a technical leader, translating high‑level objectives into actionable technical plans

EXPERIENCE REQUIRED

• Extensive experience designing, developing, and delivering AI/ML solutions end‑to‑end
• Strong software and data science fundamentals (Python essential)
• Experience building production‑grade AI systems and integrating them into customer environments
• Ability to collaborate across research, engineering, and product teams
• Experience working with large‑scale datasets and cloud‑based ML deployments
• Strong organisational skills and the ability to communicate complex ideas clearly
• Proven ability to operate independently in fast‑moving environments and manage competing priorities
• Passion for rapid prototyping, experimentation, and building high‑impact solutions

DESIRABLE EXPERIENCE

• Publications in top AI/ML/NLP or decision science venues
• Experience developing evaluation systems for LLMs or agentic models
• Experience with fine‑tuning, post‑training, or advanced model adaptation
• Familiarity with MLOps, monitoring, deployment, and large‑scale model management
• Track record of converting research prototypes into production systems

THE OFFER

• Competitive compensation (around $175,000 base depending on experience)
• Opportunity to work on deeply impactful, high‑scale AI challenges
• High degree of autonomy, technical ownership, and end‑to‑end influence
• A fast‑paced, innovation‑driven environment with strong technical peers
• Exposure to cutting‑edge modelling, LLMs, and agentic system development

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Lead Data Scientist

$175,000 to $200,000

Location: Pittsburgh, PA (Onsite)

THE ORGANISATION

A quietly scaling technology group is investing heavily in next‑generation AI capabilities. Their work centres on high‑complexity data environments, advanced analytics, and intelligent systems that surface insight, support decision‑making, and power exploratory research. The culture values depth of thinking, technical rigour, and leaders who thrive in ambiguous, evolving problem spaces.

THE OPPORTUNITY

This position will lead the development of sophisticated search, retrieval, and reasoning systems built on large‑scale datasets and advanced modelling techniques. You will act as the senior technical authority architecting platforms, shaping long‑term strategy, and mentoring a high‑calibre team across both Data Science and AI Engineering.

The role blends deep research, hands‑on modelling, system design, and leadership. Expect to define the roadmap for how information is indexed, retrieved, ranked, explored, and transformed into actionable outcomes. This is a position for someone who enjoys building from first principles, driving technical direction, and delivering complex AI capabilities end‑to‑end.

WHAT YOU’LL LEAD

• Designing and building advanced retrieval, ranking, and AI‑driven research systems
• Setting the technical strategy and multi‑year roadmap for search, knowledge exploration, and agentic reasoning capabilities
• Architecting large‑scale pipelines combining embeddings, traditional search methods, knowledge graphs, and hybrid retrieval techniques
• Developing conversational exploration tools, structured reasoning systems, and intelligent query‑understanding models
• Acting as the principal technical contributor on high‑impact projects, while also coaching and elevating senior engineers and scientists
• Collaborating with product and engineering to translate open‑ended problem statements into clear, scalable technical plans
• Establishing best practices across experimentation, modelling, evaluation, and model lifecycle management
• Bringing cutting‑edge research (LLMs, retrieval, agentic behaviours, multimodal embeddings, etc.) into production environments
• Leading workshops, technical discussions, and internal knowledge‑building initiatives

WHAT YOU BRING

• 7+ years’ experience in applied Data Science or AI research within a production‑focused environment
• Background in search/retrieval, ranking systems, embeddings, or related areas
• Expertise in building and scaling RAG pipelines, hybrid retrieval architectures, or advanced indexing strategies
• Strong ability to design and evaluate multimodal embedding models, vector‑based retrieval, and graph‑driven systems
• Deep experience with ranking and reranking architectures (bi‑encoders, cross‑encoders, multi‑tower structures)
• Strong Python engineering fundamentals and experience deploying complex AI systems
• Experience with reasoning frameworks, orchestration approaches, or agentic system design
• Ability to guide high‑impact initiatives from ideation through to production release
• Strong communication skills and the ability to influence technical and non‑technical stakeholders

NICE TO HAVE

• Research publications or recognised contributions to AI/ML/NLP communities
• Experience in fine‑tuning or post‑training large models
• Familiarity with evaluation methods for complex retrieval and agentic systems
• Experience working with large‑scale cloud environments and MLOps frameworks
• Proven ability to transition research prototypes into stable, enterprise‑grade products

THE OFFER

• Competitive compensation
• Ownership of a foundational AI capability within a rapidly scaling technical environment
• Autonomy to shape long‑term direction, architecture, and technical standards
• Opportunity to work on complex, meaningful challenges with a highly skilled AI team

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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.

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AI Scientist / Research Engineer (Applied Research)
Location: New York City
Remote: Hybrid (minimum 3 days on-site)
Salary: Top-of-market base salary + equity
Visa: No sponsorship

Company

AI-driven healthcare technology company building a next-generation platform to automate complex revenue. With access to real-world, high-stakes datasets, the company focuses on deploying cutting-edge machine learning research directly into production environments.

The Role

• Conduct applied machine learning research on large-scale, real-world healthcare data.
• Design and train advanced models focused on explainability, reinforcement learning, and long-context information retrieval.
• Move rapidly from research concepts to production-ready systems with measurable business impact.
• Design experiments, evaluate models, and contribute end-to-end code from prototype to deployment.
• Collaborate closely with MLOps, product, and engineering teams to operationalize research outcomes.

Desired Profile

• PhD in Computer Science, Machine Learning, Informatics, or a closely related field.
• 3+ years of industry or postdoctoral experience in applied ML research.
• Strong publication record at top-tier venues such as NeurIPS, ICML, EMNLP, MLHC, CHIL, or equivalent.
• Hands-on experience building novel architectures and pipelines using PyTorch, TensorFlow, or JAX.
• Background in one or more of the following: model interpretability, reinforcement learning, retrieval-augmented generation, or long-context retrieval.

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Senior MLOps Engineer
Location: United States (NYC, Austin, San Francisco preferred)
Remote: Hybrid (2-3 days on-site in major hubs) or Full Remote (US-based
Salary: Competitive base salary + equity
Visa: No sponsorship

Company

High-growth Series B AI startup transforming one of the world’s largest and least digitized industries. The company builds AI-powered platforms and autonomous agents used by thousands of professionals in real-world operational environments. Backed by top-tier venture capital firms, the organization is entering a major scale-up phase, deploying production-grade AI systems across complex workflows and large enterprise customers.

The Role

• Design and manage infrastructure for distributed model training using modern cloud and orchestration tools.
• Deploy and operate machine learning models using Docker, Kubernetes, ECS, and scalable serving frameworks.
• Integrate ML workflows into CI/CD pipelines to support rapid experimentation and reliable deployment.
• Build and maintain robust data and ML pipelines using orchestration tools such as Prefect or Airflow.
• Implement experiment tracking, observability, and monitoring across the full ML lifecycle.

Desired Profile

• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related technical field.
• 5+ years of experience in MLOps or ML Platform Engineering, including large-scale production deployments.
• Strong expertise with AWS cloud infrastructure, Docker, Kubernetes, and modern MLOps tooling.
• Hands-on experience managing GPU/CPU workloads for Computer Vision, NLP, or LLM-based systems.
• Strong communication skills and ability to operate autonomously in a fast-paced startup environment.

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