AI/ML Engineer Jobs

Our client, an AI-driven organization impacting the ecommerce market, is hiring an experienced AI/ML Engineer to join their team in Los Angeles, California. The successful candidate will lead the design and implementation of AI verification pipelines, develop robust evaluation systems and deliver production-ready features impacting millions of users.


Responsibilities

• Lead the architecture and implementation of AI verification pipelines to ensure robust, reliable model performance.

• Design, build and maintain evaluation infrastructure for AI systems at scale.

• Develop production-ready AI features that are deployed to millions of users.

• Create reasoning systems that convert probabilistic AI outputs into deterministic, auditable recommendations.

• Collaborate with cross-functional teams to integrate AI-native products into broader platforms.

• Continuously monitor, test and improve AI systems to maintain performance, security and reliability.

Skillset

• Deep expertise in machine learning, AI verification and evaluation frameworks.

• Strong experience with probabilistic modeling, reasoning systems and knowledge graphs.

• Proficiency in Python and modern ML/AI libraries (e.g. TensorFlow, PyTorch, JAX).

• Experience building production-scale AI systems that serve millions of users.

• Strong understanding of software engineering principles: version control, CI/CD, testing, and deployment.

• Familiarity with adversarial testing, verification pipelines, and AI auditing.

• Experience in AI-native product design and implementation.

• Knowledge of cloud platforms (AWS, GCP, or Azure) for scalable AI infrastructure.

• Research experience in AI interpretability, explainability or safety is a bonus.

Benefits

• Salary: $350k - $450k DOE.

Our client, a fast-growing AI startup, is hiring an AI/ML Engineer to join their team in New York. The successful candidate will focus on building the core Copilot product, with ownership across the full ML lifecycle - from data pipelines and model training to embeddings, retrieval, serving and continuous iteration in production.


Responsibilities

• Design, develop and deploy production-grade Machine Learning systems in Python, moving well beyond experimentation and notebooks.

• Take ownership of key components of the NLP and LLM stack, including embeddings, retrieval pipelines, RAG architectures and targeted fine-tuning.

• Build and iterate on recommendation and ranking models that surface who users should engage with and when.

• Work hands-on with vector databases and similarity search to drive relationship intelligence.

• Implement and maintain ML tooling for training, versioning, monitoring and evaluation.

• Collaborate closely with founders, product and engineering to translate ideas into shipped, measurable product capabilities.

• Integrate ML models into production APIs within a TypeScript / Nest.js–heavy environment.

• Continuously optimise latency, cost and performance, including model routing, caching, distillation and quantisation.

Skillset

• Minimum of 3 years of experience building and deploying production ML systems using Python, PyTorch or TensorFlow and scikit-learn.

• Hands-on NLP and LLM experience, including HuggingFace Transformers, embeddings, sentence-transformers and RAG architectures.

• Experience working with both proprietary models (e.g. OpenAI) and open-source LLMs (e.g. Llama, Mistral).

• Strong foundation in classical machine learning, including classification, ranking, supervised and unsupervised learning, and XGBoost or LightGBM.

• Experience with MLOps and infrastructure, such as experiment tracking, model versioning, Docker/Kubernetes, SageMaker or similar systems.

• Practical experience with vector databases, including Pinecone, Qdrant, Weaviate or comparable platforms.

• Strong software engineering fundamentals, with experience integrating ML models into reliable, production-grade systems.

Benefits

• Salary: Circa $250k.

• Equity.

• Health, dental and vision insurance.

Our client, a fast-growing healthcare organization, are hiring a Machine Learning Engineer to join the team in New York or San Francisco. The successful candidate will play a key role in shaping the future of conversational AI by driving meaningful improvements in patient outcomes and transforming the way healthcare systems engage and communicate.


Responsibilities

• Develop and implement machine learning models tailored for SMS and voice-enabled conversational AI.

• Create scalable pipelines to support data ingestion, model training and real-time deployment.

• Fine-tune large language models using healthcare-focused datasets to enhance accuracy and relevance.

• Collaborate with full-stack engineering teams to seamlessly integrate AI capabilities into core product experiences.

• Lead the full lifecycle of model deployment, including monitoring, troubleshooting and iterative optimization.

• Continuously explore emerging AI/ML technologies and healthcare innovations to keep their solutions cutting-edge.

 

Skillset

• At least 4 years of experience in AI/ML engineering, with a strong focus on NLP, large language models and conversational AI.

• Proven track record of deploying ML models into production, preferably within healthcare or other regulated industries.

• Proficient in Python and experienced with ML frameworks such as TensorFlow and PyTorch.

• Strong skills in fine-tuning LLMs, prompt engineering and integrating models into real-world applications.

• Comfortable working with cloud platforms (e.g. AWS, Azure, GCP) and knowledgeable in MLOps practices for scalable deployments.

• Experience with voice and speech-based technologies, including recognition and generation.

• Hands-on background in designing and implementing conversational AI solutions.

• Exceptional analytical and communication abilities.

• Familiarity with HIPAA compliance and handling of sensitive healthcare data is a bonus.

Benefits

• Competitive Salary.

• Equity.

• Remote working.

• Comprehensive healthcare package.

Our client, an AI-driven organization in the Fintech industry, are hiring a Staff Machine Learning Engineer to join the team in Colorado. The successful candidate will will focus on building end-to-end generative AI products leveraging your deep expertise in large language models, fine-tuning techniques and reinforcement learning.


Responsibilities

• Design and build multi-agent systems that automate tasks and streamline workflows, delivering measurable operational impact.

• Develop AI co-pilots for advisors and other user personas, supporting workflows across prospecting, conversion, onboarding and client servicing.

• Create purpose-built, low-latency models for complex, multi-turn financial services interactions.

• Enable AI-driven optimisation and navigation of legacy platforms using computer-use and automation models.

• Design, fine-tune, and deploy open-source and proprietary LLMs for use cases including Q&A, summarisation, reasoning and planning.

• Build advanced Retrieval-Augmented Generation (RAG) pipelines, incorporating query rewriting, embedding fine-tuning, hybrid search, re-ranking and knowledge graphs.

• Apply reinforcement learning techniques, including RL fine-tuning methods such as PPO, DPO, and GRPO, to continuously improve model performance.

• Deploy models to production, ensuring high performance, reliability, scalability and low latency.

Skillset

• At least 5 years of experience in applied AI/ML engineering.

• Demonstrated success delivering production-grade generative AI products with large language models at their core.

• Hands-on experience with LLM fine-tuning techniques (e.g. LoRA), inference frameworks (e.g. vLLM) and advanced Retrieval-Augmented Generation (RAG) architectures.

• Strong practical expertise in reinforcement learning fine-tuning methods and supporting tooling.

• Previous experience working in an early-stage startup is a plus.

Benefits

• Salary: $170k - $220k DOE