AI/ML Engineer Jobs

Our client, an AI-driven FinTech organization, are hiring a Senior AI Engineer to join the team in Manhattan, New York. The successful candidate will work with LLMs and deploy real-world AI agents, focusing on orchestration, evaluation and reliability to ensure agents perform meaningful work safely, efficiently and consistently.


Responsibilities

• Design, build and productionize end-to-end agent workflows, including APIs, tools, evaluation frameworks, monitoring and multi-step processes.

• Optimize system performance by managing latency, cost and safety controls, and building dashboards and alerts for reliability.

• Evaluate and compare models, hosting solutions and prompt strategies, implementing guardrails as needed.

• Measure outcomes, run A/B tests and iterate to improve task success and overall system effectiveness.

• Collaborate with product and design teams to develop and ship innovative interaction patterns.

Skillset

• At least 3 years of experience building AI/ML systems, preferably with LLMs or agentic workflows.

• Strong programming skills in Python, including libraries like NumPy, PyTorch or TensorFlow.

• Experience designing and integrating APIs, microservices and evaluation frameworks.

• Knowledge of workflow orchestration, multi-step planning and memory/retrieval systems.

• Familiarity with cloud platforms (AWS, GCP, Azure) and containerized environments (Docker, Kubernetes).

• Strong problem-solving skills with the ability to make informed system and code-level decisions.

• Experience with monitoring, instrumentation and A/B testing to optimize outcomes.

• Excellent collaboration and communication skills.

Benefits

• Salary: $160K–$200K

• Stock options.

• Health, dental and vision insurance.

• 401k with 3% automatic contribution.

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.

• Design and fine-tune both open source and proprietary large language models (LLMs) for tasks including summarization, reasoning, planning and question answering.
• Build and enhance advanced Retrieval Augmented Generation (RAG) pipelines featuring embedding fine-tuning, hybrid search, reranking and knowledge graph integration.
• Develop autonomous AI agent workflows that support proactive and adaptive decision-making.
• Utilize reinforcement learning methods (such as PPO, DPO, GRPO) to continuously improve model performance.
• Create evaluation frameworks and define metrics to rigorously assess model effectiveness.
• Deploy AI models into production environments with a focus on low latency, reliability and scalability.
• Work closely with product and engineering teams to deliver comprehensive AI-powered financial solutions.

• Master’s or Bachelor’s degree with at least 5 years of professional experience in applied AI/ML engineering.
• Demonstrated success in delivering generative AI products utilizing LLMs and autonomous agent workflows.
• Practical expertise with LLM fine-tuning methods (such as LoRA), inference frameworks (including vLLM) and sophisticated RAG pipelines.
• In-depth understanding of reinforcement learning fine-tuning techniques and associated frameworks.
• Early-stage startup experience is an advantage.

• Salary: $190k - $225k DOE.
• Remote working.
• Comprehensive health, dental and vision coverage.
• Retirement benefits.