Job Description

TITLE: AI Scientist

Location:- San Francisco, CA

Duration: Fulltime

GENERAL SUMMARY:

Job Description:

Capital Markets Quantitative & Technology Services - Data AI and Research Technology (DART) team is hiring a hands-on AI Engineer to build, manage and deploy cutting edge AI solutions for Investment Research, Banking, Sales and Trading.

What will you do?

Engineer advanced AI capabilities to power Research Digitization, Banking and Global Market solutions
Evaluation and subsequent implementation of Data/Model Parallelism libraries and techniques, AI Observability & Monitoring solutions, Vector databases and inference engines
Deploy, manage, performance tune and scale containerized applications using Kubernetes. Architect clusters leveraging fit for purpose hardware for AI workloads
Provide subject matter expertise in distributed and parallel computing. Analyze ML and data processing workloads to identity latency contributors, inefficient compute utilization and provide remediation recommendations
Automate AI infrastructure provisioning
Create reports for AI infrastructure usage and cost reports
Collaborate with multi-functional geographically distributed teams to drive cutting edge AI infrastructure and solutions

What do you need to succeed?

Must Have

Minimum of 2 years of hands-on AI Engineering experience
Degree in Computer Science or Engineering
Experience building, scaling, managing and monitoring ML pipelines
Experience with Python, Kubernetes, distributed computing
Solid understanding of machine learning, generative AI, agents, multi-agent collaboration, MCP servers, with focus on real-world implementation
Proficient in CI/CD principles, version control and best practices for deploying AI workloads to production.

Nice to Have

Azure Databricks, Spark, Snowflake, NVIDIA NIM, MLFlow
Experience building and deploying MCP Servers, AI Agents
Experience with any vector database.
Experience with Terraform

Best Regards

Chandra Shekhar Kumar

[email protected]

Job Tags

Full time, Part time, Seasonal work,

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