What are the responsibilities and job description for the Senior Machine Learning Engineer position at StartupTAP?
About the Company
Our client is a large, well-established financial services firm with a long track record and significant assets under management. The company has been around for decades and is known for taking a long-term, disciplined approach to how it invests.
About the Role
This is a senior-level engineering role on a newly formed AI team with a mandate to build something meaningful from the ground up. The work sits at the intersection of ML engineering and platform architecture, with real influence over technical direction and product decisions.
You'll work closely with a Senior Software Engineer as co-leads on design and execution, and collaborate directly with highly engaged internal stakeholders who rely on these tools daily.
What You'll Be Doing
- Designing and building a scalable ML platform with reusable, plug-and-play components across LLMs, agent frameworks, and multi-source data pipelines
- Taking end-to-end ownership of projects from architecture through production and ongoing operations
- Collaborating directly with internal business stakeholders to understand needs and translate them into well-structured technical solutions
- Contributing to decisions about tools, frameworks, and overall technical direction; the approach is still being shaped and the right person will help define it
- Holding a high bar for code quality, testing, and reliability
- Communicating clearly and confidently with both technical and non-technical stakeholders, including senior leadership
What You'll Bring
- 8-10 years of professional software engineering experience with strong proficiency in Python and/or TypeScript
- Demonstrated experience building large-scale production systems with solid architectural foundations
- Hands-on experience with LLMs, agent frameworks, and RAG or multi-source data pipelines
- Strong command of system design, APIs, distributed systems, and cloud-native development on AWS
- Familiarity with MLOps practices for deploying and monitoring ML systems in production
- The ability to hold your own in technical and non-technical conversations, handle direct feedback, and communicate trade-offs clearly to a range of audiences
- Proven ability to own projects independently, influence product direction, and drive things to completion
Nice to Have
- Experience with AI-assisted writing tools, document ingestion pipelines, or data synthesis systems
- Familiarity with agent orchestration frameworks and emerging GenAI tooling
- Exposure to model evaluation, monitoring, and performance trade-off analysis
- Experience with PyTorch, HuggingFace, or similar frameworks
- Comfort reading research papers and translating ideas into practical implementations
Locations Seattle, WA | Irvine, CA | Los Angeles, CA
Salary : $225,000 - $300,000