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Senior Machine Learning Engineer

Location: Fully Remote (Hybrid option in NYC)
Compensation: $190,000-$200,000 + Equity
Type: Full-Time

About the Company
We are partnering with a fast-growing, profitable SaaS company that is redefining programmatic advertising through AI-driven solutions. Their platform empowers brands to deploy custom algorithms across major DSPs (The Trade Desk, DV360, Meta, YouTube), enabling smarter, real-time ad-buying decisions. Backed by leading industry investors, this company is building ML infrastructure and solving problems that don’t have off-the-shelf solutions.

Why Join?

• Work on distributed ML infrastructure using Ray + PyTorch on Databricks.
• Build solutions that create a new software layer in ad-tech.
• Flexible working hours, fully remote, and equity participation.
• Opportunity to grow into Principal ML Engineer later this year.

Role Overview

As a Senior Machine Learning Engineer, you’ll own the ML lifecycle end-to-end, focusing on productionization and robust MLOps practices. You’ll work closely with data science and engineering teams to deploy models at scale and build automation for training, inference, and observability.

Key Responsibilities

• Deploy ML models into production using CI/CD best practices.
• Monitor and manage ML drift; retrain models as needed.
• Build automation for ML lifecycle (training, inference, observability).
• Contribute to internal API development for future projects.
• Collaborate across teams to productionize models for client and internal use cases.

Must-Have Skills

• Strong experience with CI/CD (GitHub Actions, build automation, packaging).
• Expertise in MLOps (MLflow, model versioning, monitoring).
• Hands-on with Databricks (Delta Lake, Unity Catalog, Asset Bundles).
• Proficient in Python and PySpark.
• 3-6 years of relevant experience.

Nice-to-Have Skills

• Kubernetes and containerized environments.
• API development exposure.
• Distributed training (Ray) and observability tools (Prometheus, Grafana).
• Familiarity with embedding models and Databricks Clean Room.

Screening Process

1. Intro (with Director of ML or Senior Engineer) + short live coding exercise.
2. Take-home exercise (CI/CD-focused).
3. Final interview with leadership.
4. CEO check-in.

Interested?
Apply now to join a team building brand-new solutions in ad-tech and work with technologies like PyTorch, Ray, Databricks, and MLflow.

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Senior AI Research Scientist

New York City, Hybrid

Base up tot $300,000 + Bonus + Equity

This is a standout opportunity to join a high‑growth AI organisation operating at the intersection of advanced machine learning, large‑scale distributed systems, and real‑world healthcare impact. You will work on cutting‑edge research challenges while directly influencing production systems that support mission‑critical workflows across the healthcare ecosystem.

The Company

They are an AI‑driven healthcare technology organisation building next‑generation platforms for automating complex revenue and administrative processes. Operating with the agility of a startup and the scale of an established enterprise, they combine access to significant compute resources, extensive real‑world healthcare data, and a mandate to deploy AI at nationwide scale. Their environment is deeply technical, fast‑moving, and impact‑focused, offering the chance to work alongside strong research, engineering, and product teams.

The Role

You will operate as a Senior AI Research Scientist, working end to end across ideation, experimentation, and production.

Key responsibilities include:

• Designing and training novel model architectures using PyTorch, TensorFlow, or JAX.
• Conducting applied research in areas such as long‑context retrieval, interpretability, reinforcement learning, and retrieval‑augmented generation.
• Running large‑scale experiments and evaluations on distributed GPU infrastructure.
• Contributing to deployment‑ready systems in close partnership with MLOps and ML Engineering teams.
• Translating research insights into measurable improvements across real‑world workflows.
• Staying engaged with the latest literature while building solutions that can be deployed at production scale.

Your Skills and Experience

You will bring:

• Strong capability in deep learning frameworks such as PyTorch, TensorFlow, or JAX.
• Proven experience developing and evaluating novel ML architectures or pipelines.
• Expertise in at least one of the following areas: interpretability, reinforcement learning, long‑context modelling, information retrieval, or retrieval‑augmented generation.
• Confidence working with large‑scale distributed training tools such as Ray, Lightning, or FSDP.
• A solid publication track record in reputable machine learning venues.
• The ability to work hands‑on, end to end, from research exploration through to implementation.
• A collaborative mindset suited to a highly technical, fast‑moving environment.

What They Offer

• Competitive bonus structure
• Long‑term incentive plan
• Hybrid working model with three days per week onsite
• Comprehensive health coverage
• Flexible paid time off
• The chance to influence systems operating at nationwide scale and contribute to meaningful change in the healthcare sector

How to Apply

If you are interested in this Senior AI Research Scientst position, please apply with your CV for immediate consideration.

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Lead or Senior AI Engineer

London (Hybrid, 3 days per week)

The Company
They are a well-established international organisation operating across global markets, known for delivering high-quality information and insights. With a strong focus on innovation, they have recently launched an internal AI lab to explore cutting-edge applications of generative AI. This team operates with high autonomy, working closely with stakeholders across product, engineering, and domain specialists to create impactful AI solutions.

The Role

• Lead or contribute to the design and development of AI-driven products across text, audio, and conversational interfaces
• Build and iterate on prototypes exploring areas such as voice AI, speech processing, and multimodal systems
• Define technical architecture and make key decisions on models, tools, and frameworks
• Evaluate AI systems and establish robust frameworks for performance, quality, and usability
• Collaborate with cross-functional stakeholders including product, engineering, and subject matter experts
• Translate experimental ideas into scalable product workflows and user experiences

Your Skills and Experience

• Strong commercial experience building with modern generative AI systems
• Solid engineering capability with an ability to prototype and develop production-ready solutions
• Experience working across LLMs, retrieval systems, and agentic workflows
• Knowledge of audio and speech technologies such as text-to-speech, voice AI, or dialogue systems
• Experience designing evaluation frameworks for AI systems
• Strong understanding of AI architecture, orchestration frameworks, and MLOps practices

What They Offer

• Opportunity to work in a high-autonomy AI lab environment
• Exposure to greenfield AI product development
• Strong visibility and impact across senior stakeholders
• Hybrid working with a London office

How to Apply
If you are interested in building and shaping AI-powered products in a high-impact, innovation-focused environment, please apply to find out more.

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Lead AI Engineer
London (Hybrid, 2 days in Soho)

This is a rare opportunity to step into a genuinely business-critical AI leadership role within a large, complex organisation at an early stage of its AI journey. You will have the mandate to shape how AI is built, governed and scaled across the business, with a clear focus on real operational impact rather than experimentation.

The Role

• Take ownership of the end-to-end AI strategy across the organisation, from architecture and tooling through to governance and delivery
• Design, build and productionise LLM-powered workflows and AI-enabled systems used internally across operations
• Identify, scope and deliver new AI use cases that solve tangible business problems
• Build and evolve AI infrastructure without predefined blueprints, making informed architectural decisions
• Partner closely with non-technical stakeholders to translate business needs into scalable AI solutions
• Establish best practices across MLOps, DevOps and responsible AI at enterprise scale

Your Skills & Experience

• Strong software engineering foundations with deep backend experience
• Commercial experience building and deploying AI or LLM-based systems into production environments
• Excellent data fundamentals with the ability to bridge data science and applied AI engineering
• Hands-on expertise across cloud platforms, MLOps, DevOps and modern software engineering principles
• Proven ability to operate at enterprise scale, balancing speed, quality and governance
• Confident communicator who can engage senior stakeholders and operate in ambiguous environments

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This is an opportunity to work on real-world AI applications from concept through production, leveraging the latest advancements in large language models, conversational AI, retrieval systems, and intelligent automation. The ideal candidate is a hands-on builder with recent experience deploying production-grade GenAI solutions and thrives in a fast-paced, collaborative environment.

Responsibilities

• Design, prototype, and deploy Generative AI solutions across customer-facing and internal business applications.
• Develop and optimize applications powered by large language models (LLMs), vector databases, prompt engineering techniques, and Retrieval-Augmented Generation (RAG) architectures.
• Build, deploy, and maintain AI-powered chatbots and virtual assistants, ensuring scalability, reliability, security, and compliance.
• Lead the development of AI agents for both digital and voice-based experiences, supporting real-time interactions for customers and employees.
• Evaluate, integrate, and implement third-party AI platforms, APIs, and emerging technologies to accelerate innovation and business value.
• Create proof-of-concept applications to assess new use cases such as document processing, classification, summarization, knowledge management, and workflow automation.
• Optimize prompts, model configurations, and orchestration frameworks to improve performance, accuracy, and cost efficiency.
• Partner closely with data, platform, and MLOps teams to ensure robust deployment processes, monitoring, observability, and governance practices.
• Collaborate with product managers, engineers, and business stakeholders to translate user needs into scalable AI solutions.
• Contribute to architectural discussions and establish best practices for enterprise AI adoption and integration.

Qualifications

• Bachelor’s degree in Computer Science, Data Science, Statistics, Engineering, or a related technical field.
• 6+ years of experience in AI/ML engineering, software engineering, data engineering, or natural language processing, including recent hands-on work with Generative AI and LLM-based applications.
• Demonstrated success building and deploying production-grade AI chatbots, assistants, or conversational AI solutions within the last two years.

Required Skills

• Advanced Python programming skills and experience with modern AI frameworks and libraries such as LangChain, Hugging Face, OpenAI, Transformers, or similar technologies.
• Experience working with vector databases such as Pinecone, Weaviate, Chroma, FAISS, or equivalent platforms.
• Strong understanding of RAG architectures, prompt engineering, model evaluation, API orchestration, and LLM optimization techniques.
• Solid SQL skills and experience working with cloud-based data platforms and large-scale datasets.
• Ability to operate effectively in cross-functional teams and collaborate with product, engineering, analytics, and external partners.
• Strong communication skills with the ability to explain complex AI concepts and outcomes to both technical and non-technical audiences.

Preferred Qualifications

• Experience working in highly regulated industries such as financial services, healthcare, insurance, or telecommunications.
• Hands-on experience developing voice AI, speech-enabled assistants, or conversational systems integrated with telephony platforms.
• Familiarity with modern data stack technologies, including cloud data warehouses, transformation tools, and data orchestration frameworks.
• Experience integrating AI solutions with CRM, customer service, or workflow management platforms.
• Exposure to document intelligence use cases including OCR, information extraction, summarization, semantic search, and personalized recommendations.
• Experience supporting customer-facing applications, contact center technologies, or enterprise-scale service operations.

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ML Scientist / Researcher

Oncology AI · Foundation Models · Life Sciences

Remote

About the Role

We are building foundation models trained on human tumor biology – one of the most consequential and technically demanding challenges at the intersection of AI and medicine. As an ML Scientist, you will be a core research contributor designing and training these models across multimodal omics datasets, partnering closely with biologists and fellow research scientists to advance the state of the art in oncology AI.

This is a research-forward role for scientists who want their work to matter. We are looking for people with a track record of research excellence – those who have gone deep on model architecture, training dynamics, and rigorous experimental design. If you have built models from the ground up and published findings, we want to talk.

What You’ll Do

• Design and train large-scale foundation models on multimodal biological datasets, including genomics, transcriptomics, and other omics modalities
• Collaborate deeply with computational biologists, research scientists, and domain experts to translate biological questions into tractable modeling problems
• Drive the full research lifecycle: hypothesis formation, experimental design, model development, and rigorous analysis of results
• Contribute to agentic AI systems that reason over complex biological data
• Communicate findings internally and, where appropriate, through peer-reviewed publication

What We’re Looking For

Must-Haves

• Strong research background, typically evidenced by a PhD in machine learning, computational biology, statistics, physics, or a related quantitative field – or equivalent industry research experience
• Demonstrated ability to build and train models end-to-end, including experimental analysis and iteration
• Research excellence: first-author publications at top ML, AI, or computational biology venues are a strong positive signal
• Deep familiarity with foundation model concepts: pretraining, self-supervised learning, attention mechanisms, and large-scale training
• Comfort working at the intersection of biology and machine learning – even without a formal biology degree

Nice-to-Haves

• Experience with biological or omics data (genomics, proteomics, pathology imaging, etc.)
• Prior work in multimodal learning or multi-omics integration
• Familiarity with agentic AI systems or tool-use frameworks
• Background in oncology or disease biology

What This Role Is Not

This is not a production ML engineering or MLOps role. We are not looking for candidates whose primary experience is model deployment, serving infrastructure, or engineering-heavy systems work. The emphasis here is firmly on research depth and model development.

Compensation & Location

Base Salary: $250,000 – $288,000 (depending on experience) + equity

Location: Remote-friendly; office in South San Francisco, CA

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AI Engineer

London (Soho, hybrid, 2 days per week)

The Company
They are a well established media business with a significant infrastructure footprint spanning physical and digital assets. Operating across multiple verticals, they have a strong market position and continue to grow through investment and acquisition. The organisation is now rebranding and investing heavily in digital, data, and AI capabilities to modernise operations and unlock new efficiencies. Their current focus is on building internal AI use cases, with future plans to expand into customer facing products.

The Role
You will be responsible for shaping and delivering AI solutions from concept through to production within a growing function.
Key responsibilities include:
* Designing and implementing AI solutions to improve operational efficiency
* Defining LLM architecture and selecting the appropriate AI stack
* Building and deploying AI tools such as assistants and workflow automation solutions
* Developing document processing capabilities to support real world use cases such as contract and tender analysis
* Working within an Azure cloud environment and applying best practices in MLOps and DevOps
* Collaborating closely with product teams and senior leadership, including acting as a key partner to the Director of AI

Your Skills and Experience
* Strong commercial experience in AI engineering or machine learning, ideally evolving from a data science background
* Proven experience building and deploying LLM based applications in production environments
* Experience working with cloud platforms and modern deployment practices, ideally within Azure
* Knowledge of DevOps or MLOps principles
* Ability to define architecture and build AI solutions end to end
* Strong communication skills and experience working with a range of stakeholders

What They Offer
* Hybrid working with a central London office
* Opportunity to shape AI strategy at an early stage
* Exposure to large scale, real world AI challenges
* Clear progression as the AI function continues to grow

How to Apply
If you are interested in building and scaling AI solutions within an enterprise environment, apply now to find out more.

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Senior AI and Machine Learning Lead
Amsterdam | €95,000 to €120,000 plus bonus

This is a senior leadership role for someone who wants to shape how AI and machine learning drive real product outcomes. You will sit at the centre of product and technology, setting the direction for applied AI across multiple teams while remaining close to the technical detail. The role offers the chance to influence strategy, operating models and culture as the organisation moves towards an AI-first approach.

The Company
They are a highly product-led, technology-driven organisation operating at scale in a digital marketplace environment. Data, machine learning and AI are core to how products are built and evolved. The organisation invests heavily in modern data platforms and encourages thoughtful experimentation with emerging technologies. Collaboration between product, engineering and data teams is a key part of how they deliver impact.

The Role

• Lead and develop a team of data scientists embedded within product teams, setting a high bar for technical quality and delivery.
• Define and own the machine learning and AI strategy, aligning it with long-term product and business goals.
• Champion an AI-first mindset, identifying where traditional ML, generative AI or hybrid approaches create the most value.
• Guide the full lifecycle of ML and AI solutions, from experimentation through to robust production systems.
• Drive improvements in MLOps, model evaluation practices, development workflows and coding standards.
• Make informed build versus buy decisions, evaluating vendors and third-party solutions where appropriate.
• Partner closely with product, engineering and business stakeholders to translate opportunities into measurable impact.
• Stay ahead of developments in ML, generative AI and the wider AI landscape, turning trends into actionable direction.

Your Skills and Experience

• Strong commercial experience as a data scientist or machine learning engineer, with deep understanding of core ML and AI concepts.
• Proven ability to lead and grow high-performing data science or ML teams.
• Experience delivering and maintaining large-scale ML systems in production, including monitoring and iteration.
• Solid understanding of modern MLOps practices and data platforms.
• Practical knowledge of generative AI and large language model applications, with clear judgement on where they add value.
• A strategic mindset, able to connect technical decisions to product and business outcomes.
• Confident communicator, comfortable influencing senior stakeholders and making decisions with incomplete information.

What They Offer

• Salary between €95,000 and €120,000 plus a performance-related bonus.
• A senior role with real ownership over AI and ML direction across the organisation.
• The opportunity to work on high-impact, user-facing products at scale.
• A collaborative culture that supports learning, experimentation and career progression.

How to Apply
Apply now to find out more about this Senior AI and Machine Learning Lead opportunity in Amsterdam.

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AI Engineering Lead

UK Remote

The Company

They are a global testing, inspection, and compliance group operating across a diverse set of regulated industries. The organisation has scaled significantly through acquisition and continues to invest in long term, sustainable growth. With a portfolio of specialist businesses, they provide critical compliance and inspection services across multiple sectors. The business is at an early stage in its AI journey, with strong backing and clear intent to invest in this space.

The Role

You will lead the definition and execution of a group wide AI strategy, with full ownership over delivery and direction. Your responsibilities will include:

* Defining and implementing the organisation’s AI strategy across multiple business units

* Identifying and prioritising high impact use cases that deliver measurable value

* Designing and building AI systems, from concept through to production deployment

* Developing LLM based applications, including document processing and workflow automation

* Establishing standards for AI governance, tooling, and best practice

* Working closely with senior stakeholders to align on transformation initiatives

* Driving adoption and ensuring consistent approaches across a decentralised group structure

Your Skills and Experience

You will bring strong commercial experience in AI and software engineering, with the ability to operate both strategically and hands on. Key requirements include:

* Proven ability to deliver AI or machine learning solutions into production environments

* Strong programming capability in Python and modern AI frameworks

* Experience working with LLMs and tools such as LangChain or similar ecosystems

* Expertise in building applications including chatbots, document processing, or agent based systems

* Solid understanding of MLOps, scalable architecture, and deployment best practices

* Comfortable working in ambiguous, greenfield environments with high autonomy

* Strong stakeholder engagement skills, with experience influencing senior leaders

What They Offer

They offer a highly competitive salary with flexibility for the right candidate, alongside a performance related bonus and private medical cover. You will benefit from a remote first working model, with access to senior leadership and the opportunity to shape AI strategy at an enterprise level. This is a high impact role with clear scope for progression as AI capability matures across the group.

How to Apply

If you are interested in leading AI innovation in a greenfield environment, apply with your CV to learn more.

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