Senior ML/AI Engineer
Location: USA (Remote)

My client is a growing HealthTech org heavily invested in being an AI-First culture.

You will get to join a new AI team to help create and build AI & ML systems across the operations of the business involving work from NLP/LLM use cases to traditional machine learning systems.

If you like solving business problems, building and owning high impact systems this could be the role for you.

You will get to build AI solutions that enhance precision care, patient engagement and operational efficiency.

Your day to day will largely involve digging into the data, identifying uses cases and building out from MVP to productionized ML systems.

Leading the design, development, and fine-tuning of large language models (LLMs), Multimodal systems, ML systems (using tools like Pytorch) and bringing them to production with MLOps frameworks.

What's in it for you?

• Lead from the front , reporting to the SVP , help scope, design and build use cases and systems
• $160k - 200k Base Salary
• Up to 10% Bonus
• Fully remote work
• Access to to a wealth of data, impactful work and autonomy.

If you are interested in learning more send your CV into us or email me anthonyh@alldus.com

Our client, an exciting Series B FinTech Startup, is hiring a Staff Machine Learning Engineer to join the team remotely. The successful candidate will design and deploy advanced machine learning models to help build interpretable, high-performing and scalable solutions leveraging data from AWS and Snowflake environments to drive impactful, data-informed decisions.


Responsibilities

• Designing, developing and deploying machine learning models to support predictive analytics across key fintech applications.

• Collaborating closely with cross-functional teams, including Data, Engineering and Product, to deliver integrated, data-driven solutions.

• Ensuring high model performance and reliability through robust data pipelines and scalable infrastructure.

• Converting model outputs into actionable insights that drive business strategy and financial inclusion outcomes.

• Mentoring and supporting fellow team members to promote a culture of technical excellence and collaboration.

• Championing best practices in MLOps, data governance and regulatory compliance across the ML lifecycle.

Skillset

• PhD or Master’s degree in Computer Science, Mathematics, Statistics or similar.

• 10+ years of relevant experience in applying AI/ML techniques within the financial services or fintech sectors.

• Extensive experience developing and deploying machine learning models for tasks such as classification, regression and forecasting.

• Strong programming proficiency in Python and SQL.

• Hands-on experience with AWS, particularly SageMaker and Bedrock, for model training, deployment and fine-tuning.

• Familiarity with model lifecycle tools like MLflow, SageMaker Model Registry or similar platforms.

• Practical experience using PyTorch, Scikit-learn and Generative AI models.

• Knowledge of Large Language Models (LLMs) and frameworks such as Hugging Face, LangChain or Mirascope.

• Solid understanding of cloud-based data architecture, including Snowflake, Amazon S3 and PostgreSQL.

• Background working in FinTech, PropTech or startup environments is a bonus.

Benefits

• Salary: $200,000 - $235,000.

• Equity.

• Remote working.

• Comprehensive health, dental, and vision insurance.

• 401(k).

Our client, a leading FinTech organization, are hiring a Principal Machine Learning Engineer to join their Applied AI team in New York. The successful candidate will take technical ownership of a key product line, specializing in generative AI solutions that leverage large language models (LLMs) at their core.


Responsibilities

• Shape and execute the company’s AI strategy to drive continuous innovation and business growth.

• Work closely with product and engineering teams to develop comprehensive, end-to-end AI-powered products.

• Design and implement multi-agent systems that automate workflows and enhance operational efficiency.

• Develop AI-driven co-pilot tools to optimize advisor processes such as prospecting, conversion, onboarding and client servicing.

• Build tailored models to manage complex financial interactions, delivering fast, actionable insights.

• Create innovative solutions to seamlessly integrate and optimize legacy systems with modern AI technologies.

• Lead rapid zero-to-one product development cycles, including prototyping, testing and feature integration.

• Design and fine-tune both open-source and proprietary large language models for applications including question answering, summarization, reasoning and planning.

• Employ reinforcement learning methods to continually enhance model accuracy and performance.

Skillset

• Master’s or PhD degree in Computer Science, Engineering or similar.

• At least 7 years of experience in applied AI engineering, including at least 2 years in a technical leadership capacity.

• Demonstrated success delivering generative AI products based on large language models.

• Expertise in creating agentic workflows that enable autonomous AI functions.

• Previous experience in early-stage startups or building products from the ground up.

Benefits

• Salary: $200,000 - $250,000

• Equity.

• Comprehensive health, dental and vision insurance.

• Retirement benefits.

Our client, a leading Fintech company, are hiring a Staff Machine Learning Engineer to join their Applied AI team remotely. The successful candidate will be responsible for developing and deploying AI-powered multi-agent systems, human-in-the-loop co-pilots, specialized financial models and seamless legacy system integrations to automate processes, improve workflows and optimize existing financial technologies.


Responsibilities

• 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.

Skillset

• 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.

Benefits

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

Our client, an exciting AI-driven company, are hiring a Machine Learning Engineer to join the team in Seattle, Washington or Palo Alto, California. The successful candidate will be instrumental in building and scaling the infrastructure behind the company’s open AI platform, leveraging strong platform engineering skills and a solid machine learning background to support everything from training workflows to production deployment.


Responsibilities

• Develop and sustain reliable systems for training, deploying and scaling AI models.
• Build and enhance workflows for data preparation, model training, evaluation and deployment.
• Identify and resolve performance bottlenecks to ensure smooth operation for thousands of users and contributors.
• Automate infrastructure provisioning, deployment and monitoring following DevOps best practices.
• Collaborate closely with researchers and developers, both within the company and across our open-source community.
• Contribute to the development and direction of their open-source platform and foundational AI models.

Skillset

• Extensive experience in infrastructure engineering, DevOps or cloud-native environments.
• Deep understanding of machine learning principles and practical experience with end-to-end ML workflows.
• Proficient in Python and skilled in best practices for software development.
• Practical knowledge of cloud platforms such as AWS, Google Cloud or Azure.
• Experience with distributed computing and designing scalable systems.
• Enthusiasm for open-source development and active participation in community-driven projects.

Benefits

• Salary: $100K - $220K DOE.
• Equity.
• Comprehensive health, dental and vision insurance.