Sr Machine Learning Engineer

Position: Sr Machine Learning Engineer

Location:
California and New Jersey

Duration: 6 months (right to hire)

Interview Process: 2-3 interview rounds (intro, coding, architecture)

Summary:

As a Sr Machine Learning Engineer, you will be independently engineering Agentic AI Systems, and partner with Data Scientists, Data Engineers, Data Analysts, Dev Sec Ops  and other professionals helping to implement traditional models and agentic AI systems to deliver stability, producibility, scalability and integration with other products and services. You will also participate in architectural capabilities that combine large language models with semantic knowledge layers, knowledge graphs, ontologies, and deterministic reasoning to support accurate, explainable and governable business decisions.

You will implement capabilities to solve sophisticated business problems, deploy innovative products, services, and experiences to delight our customers! In addition to advanced technical expertise and experience, you will bring excellent problem solving, communication and teamwork skills, along with agile ways of working, strong business insights, an inclusive leadership attitude and a continuous learning focus on all that you do.

• Architect, Design and Development and Deployment of ML models and Agentic AI systems that solve real-world business problems, while working in collaboration with the Product and Data Science teams; remove complex technical impediments
• Design and implement semantic knowledge layers that represent domain entities, relationships, taxonomies, ontologies and business rules for use by LLM and agentic applications.
• Build knowledge graph, Graph RAG capabilities that combine vector retrieval with entity resolution, graph traversal, multi-hop reasoning, and relationship aware context retrieval.
• Solve complex problems by writing and testing application code, developing and validating ML models and Agentic AI, and automating tests and deployment using LLM tools like Claude Code.
• Leverage cloud-based architectures and technologies to deliver optimized ML models, semantic reasoning and Agentic systems at scale.
• Construct optimized data, ingestion, knowledge graph, semantic layer and memory pipelines to feed ML models and Agentic systems
• Define approaches for ontology lifecycle management, schema evolution, temporal knowledge, data lineage, graph freshness, and synchronization with source systems.?
• Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code
• Bring a strong understanding of relevant and emerging technologies, provide input and coach team members and embed learning and innovation in the day-to-day
• Work on complex problems in which analysis of situations or data requires an evaluation of intangible variables.
• Use programming languages including but not limited to Python, C++, SQL, Cypher, Gremlin or other graph query languages.

• Bachelor of Computer Science or Engineering or experience in related fields
• Ability to coach others with minimal guidance and effectively leverage diverse ideas, experiences, thoughts and perspectives to the benefit of the organization
• Experience with agile development methodologies and Specification-Driven Development (SDD)
• Knowledge of business concepts, tools and processes that are needed for making sound decisions in the context of the company's business
• Ability to learn new skills and knowledge on an on-going basis through self-initiative and tackling challenges
• Excellent problem solving, communication and collaboration skills