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Senior AI/ML Engineer About the Role A Silicon Valley-based cloud system integrator working with AWS, Google, and Databricks. We're looking for a Senior AI/ML Engineer to join our flagship AI Platform for life sciences — supporting companies like Pfizer, Moderna, and Novartis in accelerating drug discovery through cloud and AI. You'll help design and deploy production AI systems, from autonomous agents to classical ML pipelines and enterprise AI gateways. What You'll Do Build and deploy multi-agent AI systems (LangGraph, AutoGen, or similar), including tool-calling and MCP (Model Context Protocol) servers/clients. Deploy AI Gateway infrastructure to manage LLM routing, cost, and security across providers (OpenAI, Anthropic, Bedrock, Vertex). Build end-to-end deployment pipelines (Databricks/SageMaker) with monitoring for drift and performance. Design RAG pipelines and fine-tune open-source LLMs (LoRA/QLoRA) for domain-specific use cases. Lead architecture reviews, mentor on MLOps best practices, and collaborate with data engineers on lakehouse pipelines. Participate in daily Scrum with a globally distributed team. What You Bring 5+ years in software/AI engineering, including 3+ years focused on AI/ML in production. 2+ years deploying classical ML models and/or LLM-based systems at scale. Hands-on experience with AI agent frameworks and/or AI Gateway infrastructure. Strong Python skills; working knowledge of TypeScript/Node.js for backend APIs. Experience with Databricks (Spark, Delta Lake, MLflow, Unity Catalog) and AWS (ECS, Lambda, SageMaker, S3). Excellent English communication — able to explain ML systems to both technical and non-technical stakeholders. Comfortable working autonomously in a remote team (9 AM–5 PM EST overlap required). Nice to Have AWS ML Specialty, Databricks ML Professional, or Google ML Engineer certification. Experience fine-tuning open-source LLMs (Llama, Mistral, Falcon). Familiarity with GxP/21 CFR Part 11 compliance in life sciences. Contributions to open-source AI/ML or MCP tooling. What We Offer Competitive compensation and benefits. Zero legacy infrastructure — work on cutting-edge AI systems. Training budget (certifications, hackathons, Udemy/Coursera). Access to Claude Code, Codex, Cursor, and frontier model APIs. A collaborative team at the intersection of life sciences and applied AI.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.