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Our client, an early-stage AI startup, are hiring a Founding Applied AI Engineer to join their team in New York. The successful candidate will design and build the intelligence layer that powers the company's personalisation, recommendation systems and external APIs, including transforming behavioural data into meaningful, actionable understanding of users.


Responsibilities

• Partner with founders to identify which user signals (taste, behaviour, intent, identity) drive value.

• Translate ambiguous product questions into measurable modelling problems.

• Define what "user understanding" means in a data-driven system.

• Design and implement recommendation systems including collaborative filtering, matrix factorisation, embedding models and two-tower architectures.

• Build cross-domain recommendation systems across media and consumption types.

• Develop scalable systems that convert behavioural signals into actionable user representations.

• Create trait inference pipelines and behavioural feature systems.

• Design reusable user feature abstractions for downstream products and APIs.

• Design and run A/B tests, bandit systems and offline evaluation frameworks.

• Define what is stored, inferred and exposed via context APIs, and help shape how external systems consume user context safely and effectively.

Skillset

• Strong foundation in machine learning, particularly statistical modelling and feature engineering.

• Proven experience building production recommendation systems (e.g. collaborative filtering, matrix factorisation, embeddings).

• Experience working with large-scale behavioural or interaction datasets (ads, media, e-commerce or consumer platforms).

• Strong Python skills, with comfort in research-style environments such as Jupyter notebooks and experimentation codebases.

• Deep understanding of classical ML and recommender systems, with pre-LLM or hybrid systems experience strongly preferred.

• Experience designing and running A/B tests, bandit systems or other online experimentation frameworks.

• Ability to evaluate models using rigorous statistical methods and sound experimental design.

• Familiarity with modern ML frameworks such as PyTorch, JAX or equivalent tools.

• Strong product intuition, with a focus on user impact over purely model-centric metrics.

• Ability to operate in ambiguous problem spaces and translate technical outputs into product and business decisions.

Benefits

• Salary: $180k - $250k DOE.

Our client, an innovator in the Financial Services industry, are hiring a Data Scientist to join their team in California. The successful candidate will be responsible to work at the intersection of data, engineering and fraud detection, while helping to shape and refine the company's software as it evolves to stay ahead of increasingly sophisticated cyber-attacks.


Responsibilities

• Own end-to-end development of user-facing product features, from initial concept to full launch.

• Translate research findings into practical, high-impact product enhancements.

• Collaborate and work independently to design, test and refine solutions.

• Adopt a product-first approach, turning analysis into measurable results quickly.

Skillset

• PhD degree in Computer Science, Engineering or similar.

• Minimum of 2 years' experience working in the data science field.

• Strong interest in software engineering and product development.

• Skilled at translating research insights into real-world solutions.

• Self-motivated with the ability to take ownership of projects and drive them to completion.

Benefits

• Salary: $140k - $170k.

• Remote working options.

Our client, a venture-backed AI Startup, is hiring a talented ML/AI Research Engineer to join their team in San Francisco. The successful candidate will lead the design, training, evaluation and optimization of agent-native AI systems, working at the cutting edge of LLMs, vector search, graph reasoning and reinforcement learning to build the intelligence layer on top of their enterprise data fabric.


Responsibilities

• Fine-tune and evaluate open-source LLMs (e.g. LLaMA 3, Mistral, Falcon, Mixtral) for enterprise-grade applications.

• Build and optimize RAG pipelines using tools such as LangChain, LangGraph, LlamaIndex or Dust.

• Develop and iterate on agent architectures (ReAct, AutoGPT, BabyAGI, OpenAgents) using real-world enterprise workflows.

• Design embedding-based memory systems with efficient, high-performance retrieval strategies.

• Implement reinforcement learning pipelines (RLHF, DPO, PPO) to improve agent behavior and decision-making.

• Create scalable evaluation frameworks, including synthetic evaluations, trace capture and explainability tooling.

• Own model observability, drift detection and alignment strategies across production systems.

• Optimize inference latency and GPU utilization across cloud and on-premise infrastructure.

Skillset

• Strong experience fine-tuning open-source LLMs using frameworks such as HuggingFace, DeepSpeed, vLLM, FSDP and LoRA/QLoRA.

• Hands-on experience with modern alignment techniques, including SFT, RLHF and DPO pipelines.

• Proven ability to build high-quality training datasets and robust evaluation frameworks for LLM systems.

• Deep understanding of scaling and optimization trade-offs, including batching, context windows, precision and quantization.

• Experience building and deploying production-grade RAG systems.

• Familiarity with orchestration and retrieval tools such as LangChain, LangGraph and LlamaIndex, and vector databases (Weaviate, Qdrant, FAISS).

• Experience working across structured (SQL, graph) and unstructured data sources.

• Experience designing agent-based systems with memory, tool use, and multi-step reasoning.

• Strong understanding of agent workflows (e.g. Plan-Act-Reflect), including self-correction and multi-agent systems.

• Expertise in inference and retrieval optimization, including chunking strategies, reranking, and low-latency deployment (e.g. vLLM, TGI).

Benefits

• Salary: $180k - $240k

• Equity.

Our client, a global AI and Data organisation, are hiring an AI Lead to join their growing AI Innovation Lab in Dublin, Ireland. The successful candidate will play a key role in shaping the platform, selecting the right technologies and leading teams to deliver AI solutions into production.


Responsibilities

• Take ownership of the AI platform architecture and its ongoing development.

• Assess and select best-in-class AI tools and technologies.

• Lead solution teams delivering and integrating AI across the business.

• Establish standards, best practices and governance frameworks.

• Oversee AI agent orchestration, monitoring and continuous optimisation.

Skillset

• At least 7 years of experience in software engineering.

• Strong proficiency in Python, with experience using LangChain and LangGraph.

• Solid understanding of Docker and cloud architecture (AWS preferred; Azure or GCP also considered).

• Hands-on experience with Generative AI technologies and prompt engineering.

• Proven track record of building and delivering enterprise-grade applications.

Benefits

• Competitive salary.

• Performance bonus.

• Comprehensive benefits package.

• Hybrid working - 3 days onsite, 2 days remote.

Our client, an innovator in the financial services industry, is hiring a Staff Machine Learning Engineer to join their team remotely. The successful candidate will leverage their expertise in data science and ML operations to enhance model accuracy while optimizing infrastructure for both scalability and cost efficiency.


Responsibilities

• Enhance their pricing model to boost accuracy for high-value cards while minimizing infrastructure costs.
• Refine our underwriting model to optimize cash advance disbursements while keeping risk and default rates in check.
• Own the full ML lifecycle, from model training and feature engineering to deployment and monitoring.
• Work closely with pricing experts to gain deep domain knowledge of the trading card market and drive model improvements.
• Plan and run experiments and back tests to identify and validate features that strengthen predictive performance.
• Manage AWS infrastructure and develop code for our pricing API to ensure scalable, low-latency model delivery.

Skillset

• Minimum of 10 years of engineering experience, including at least four years focused on machine learning.
• Deep expertise in Python, with hands-on experience in libraries such as scikit-learn, XGBoost and pandas.
• Strong ML Ops and infrastructure background, with experience deploying models on AWS using ECS and Docker.
• Skilled in data orchestration and workflow management using Airflow for model training and batch processing.
• Demonstrated success improving model accuracy through feature engineering and experimentation.
• Experience with Random Forest, ensemble methods, or pricing/underwriting models in marketplace or fintech environments.

Benefits

• Salary: Circa. $250k.
• Equity.
• Remote working.
• 401(k) retirement benefits.
• Competitive healthcare package.

Our client, a leading innovator in Insurance industry, are hiring an AI Engineer to join their growing team in New York. The successful candidate will play a key role in executing the company's AI strategy, along with designing, building and integrating intelligent, reliable and scalable AI-driven features into their core applications using modern web frameworks and cloud infrastructure.


Responsibilities

• Partner with product, engineering and design teams to uncover user challenges and deliver generative AI solutions using modern software development practices.

• Build end-to-end AI integrations across the full stack - frontend, backend and infrastructure - embedding intelligence directly into applications.

• Create smart search and information retrieval systems that enable users to access relevant data quickly and efficiently.

• Design and implement robust interactions with foundation models (e.g. GPT-4, Claude, Gemini) to ensure reliable and consistent performance.

• Deliver AI-powered features that uphold the highest standards of scalability, security and performance.

Skillset

• Minimum of 5 years of experience building modern full-stack web applications with Python and JavaScript/TypeScript.

• Practical experience integrating foundation models via direct API connections.

• Demonstrated ability to translate user challenges into elegant technical solutions and lead initiatives that deliver engaging AI experiences.

• Proficient across the full application stack, from frontend to backend and infrastructure.

• Knowledge of tool calling, multi-agent systems, and emerging frameworks such as Model Context Protocol (MCPs).

• Hands-on experience with Machine Learning (PyTorch, scikit-learn) and deploying proprietary or open-source models.

• Strong communication skills with a proven ability to collaborate effectively with cross-functional teams.

Benefits

• Salary: $170k - $200k

• Stock options.

• Healthcare, vision and dental insurance.