Strategic Projects Lead - Engineering

Spectrum Search; San Francisco (CA); On-site; USD 140,000 - 190,000; Full time

Job summary

Spectrum Search is partnering with a venture-backed AI company in San Francisco seeking an engineer with a life sciences background to shape how frontier AI models learn and are evaluated. You will blend technical depth with project leadership, influencing model training and assessment in a fast-paced setting.

Join a team that collaborates with top AI labs to deliver next-generation data solutions, guiding projects from scoping to delivery and working across multiple domains to drive revenue and

Qualifications

• 2-10 years' hands-on professional engineering experience (beyond internships).
• Advanced degree (MS/PhD/MD) in chemical engineering, biomedical engineering, chemistry or related field.
• Experience across multiple engineering or life sciences domains.
• Coding experience (e.g. Python) or use of simulation/analysis tools (e.g. Aspen Plus, MATLAB, COMSOL or bioinformatics pipelines).
• Exposure to CAD, circuits or chip design; familiarity with AI-assisted workflows.

Responsibilities

• Partner directly with leading AI organisations to design and deliver next-generation data solutions that push model capability forward and drive revenue.
• Coordinate highly specialised contributors across domains such as finance, software engineering and law to produce high-quality outputs at scale.
• Design dataset specifications that directly influence how frontier models are evaluated and improved.
• Take critical projects from idea to delivery, covering scoping, execution, iteration and shipping in a fast-paced environment.
• Support initiatives across the business, building, analysing, coordinating and executing wherever you're needed most.

Education

MS/PhD/MD in chemical engineering, biomedical engineering, chemistry or related field

Job description

We're working with a fast-growing, venture-backed AI company that sits at the centre of the frontier AI ecosystem. They work with the world's leading AI labs to build the specialised datasets used to train and evaluate the next generation of foundation models. This is a chance to apply your engineering background at the cutting edge of AI. You'll have real ownership, commercial impact, and exposure across the whole business.

The role

Our client is looking for an engineer from the chemical, biomedical or life sciences space to join their team. You'll combine technical depth with project leadership, shaping how frontier AI models learn and get evaluated in your field.

What you'll be doing

• Project and client management: Partner directly with leading AI organisations to design and deliver next-generation data solutions that push model capability forward and drive revenue.
• Leading expert teams: Coordinate highly specialised contributors across domains such as finance, software engineering and law to produce high-quality outputs at scale.
• Shaping how AI is trained: Design dataset specifications that directly influence how frontier models are evaluated and improved. Your judgement will help shape what these models become.
• End-to-end ownership: Take critical projects from idea to delivery, covering scoping, execution, iteration and shipping, in a fast-paced, high-stakes environment.
• Broad operational exposure: Support initiatives across the business, often several areas in the same week, building, analysing, coordinating and executing wherever you're needed most.

What our client is looking for

• 2-10 years' hands-on professional engineering experience (beyond internships)
• A background in chemical engineering, biomedical engineering, biotech, pharma or a related life sciences discipline (e.g. process design, biomedical devices, drug development)
• The ability to walk through your reasoning clearly and justify decisions or pivots using data and facts
• An advanced degree (MS/PhD/MD) in chemical engineering, biomedical engineering, chemistry or a related field
• Experience across multiple engineering or life sciences domains
• Coding experience (e.g. Python) or use of simulation and analysis tools such as Aspen Plus, MATLAB, COMSOL or bioinformatics pipelines
• Exposure to CAD, circuits or chip design
• Familiarity with AI-assisted workflows such as Claude Code or similar tools