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Senior Machine Learning Engineer

Quantiphi

On-siteNew York City, NYsenior$110k–$140kPosted 1h ago

Job description

About Quantiphi:

Quantiphi is an award-winning, AI-First global digital engineering company that helps the world’s leading Fortune 1000 organizations transform bold ideas into measurable business impact. We go beyond building innovative AI technologies—we solve the problems that matter most to our clients.

Since our founding in 2013, Quantiphi has built a proven track record of turning complex challenges into meaningful outcomes across industries.

Headquartered in Boston, with more than 4,000 professionals worldwide, we partner with global enterprises to deliver large-scale digital, cloud, and AI-driven transformation.

#SolvingWhatMatters

We are an Elite and Premier partner to Google Cloud, AWS, NVIDIA, Snowflake, and other leading technology platforms, and our work has been recognized across the industry, including:

  • 21 Google Cloud Partner of the Year awards in the past 10 years

  • 3 AWS AI/ML Partner of the Year awards

  • 3 NVIDIA Partner of the Year awards

  • 3 Snowflake Partner of the Year awards

  • Rated Leaders by Gartner, Forrester, IDC, ISG, Everest Group and other leading analyst firms

Quantiphi delivers First-in-class AI solutions across Life Sciences, Healthcare, Banking, Financial Services, CPG, Manufacturing, Energy, High-Tech, Telecommunications, etc., powered by cutting-edge Generative AI and Agentic AI accelerators.

We are also proud to be certified as a

Great Place to Work

—reflecting our commitment to our people and our culture.

For more details, visit:

Website

or

LinkedIn Page

Job Description -

Key Responsibilities -

  • Build hands-on, end to end. Design, code, test, and ship agentic AI features

  • into production — you write code every day, not just architecture diagrams.

  • Engineer agentic systems. Develop planning, retrieval, tool-use, and

  • orchestration components for the internal agentic search engine.

  • Integrate many data sources. Connect agents reliably and securely to

  • numerous internal and enterprise data sources.

  • Deliver on Google Cloud. Build, deploy, and operate solutions natively on GCP

  • (Vertex AI, GKE, BigQuery, Cloud Run, and related services).

  • Ship the user experience. Contribute to the Perplexity-style front end so end

  • users get fast, grounded, well-cited answers.

  • Own quality and evaluation. Establish evals, guardrails, observability, and

  • feedback loops to keep answers accurate and safe.

  • Operate with urgency in a fast-moving engagement — iterate quickly, unblock yourself, and drive outcomes.

Required Qualifications -

Must-Have Skills -

  • Strong, current software engineering fundamentals — clean, tested,

  • production-quality code (Python strongly preferred).

  • Demonstrated, hands-on experience building agentic AI systems (agents, tool-

  • use, planning, multi-step reasoning, RAG/retrieval).

  • Deep expertise with the Google Cloud technology stack — e.g., Vertex AI, GKE,

  • BigQuery, Cloud Run, Cloud Storage, IAM.

  • Experience integrating LLM applications with numerous, heterogeneous data

  • sources (APIs, databases, document stores, search).

  • Experience taking ML/GenAI systems to production — deployment, scaling,

  • monitoring, and reliability.

  • Breadth of knowledge across frontier models (e.g., Gemini, and other leading

  • LLM families) and when to use which.

  • Hands-on experience with open-source agentic and LLM frameworks (e.g.,

  • LangChain, LangGraph, LlamaIndex, or similar).

  • Front-end / full-stack exposure to help deliver a Perplexity-style user

  • experience.

  • Experience with evaluation frameworks, guardrails, and responsible-AI

  • practices.

  • Prior experience in regulated or enterprise environments (healthcare a plus).

Ideal Candidate Profile -

  • The right person for this team is a builder at heart — someone who is energized by

  • shipping working software, thrives in ambiguity, and raises the quality bar for

  • everyone around them.

  • Extremely hands-on: happiest in the codebase, shipping real features.

  • Bridges agentic AI and solid software engineering — not just prototypes, but

  • production systems.

  • Pragmatic and fast — comfortable with a high-tempo, fast-moving

  • engagement.

  • Strong communicator who collaborates well in person with a tight-knit pod and

  • client stakeholders.

  • Curious about the frontier — keeps up with new models, frameworks, and

  • techniques.