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Technical Lead, Product
Technical Lead, Product
Bioptimus is building the first universal AI foundation model for biology to fuel breakthrough discoveries and accelerate innovation in biomedicine. With over $75M in funding, Bioptimus is a fast-growing startup headquartered in Paris, founded in October 2023. Backed by leading venture capitalists, our team of scientists and engineers is redefining the intersection of AI and life sciences.
Role Overview
Position: Technical Lead, Product Location: Remote (outside of Paris)
About the Role
We are seeking a Technical Lead to develop a product featuring our foundation models for biology, empowering scientists and engineers. From backend services and APIs to front-end interfaces—you will own features end to end, transforming research into robust, user-friendly products. This role blends AI, systems engineering, and product excellence.
You’ll partner with Product Engineers, coordinate cross-team initiatives, and deliver reliable solutions grounded in science. This isn’t traditional management—it’s senior ownership through impactful output: shipping challenging features, setting technical standards through code and mentorship, and shaping consistent engineering practices. As we scale, leadership opportunities go to those who want them (but aren’t required).
Key Responsibilities
Product Development (End-to-End)
- Design, ship, and refine features bridging our foundation models to user capabilities (back-end services through front-end interfaces).
- Balance speed, quality, and maintainability—guaranteeing deep workflow ownership from ideation to operational delivery.
Back-End & Services
- Create scalable services (REST/gRPC APIs) to compose our biological models into actionable functionalities.
- Handle data workflows and back-end logic leveraging Python, SQL, and cloud-integrated systems.
Harnessing Model Capabilities
- Build products on top of SDK/model packages from our engineers, refining them to ensure they meet end-user needs.
Technical Leadership
- Define patterns, review standards, and guide technical decisions across ambiguous areas.
- Achieve no-code leadership: expand mentoring through deep code knowledge rather than hierarchical oversight.
AI-Native Toolset
- Use tools such as opencode/Claude to accelerate development and guide the team toward AI-assisted workflows.
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Collaboration
- Work closely with the Platform/Infrastructure and Product Engineering teams to dissect scientific, technical, and user-centric requirements.
What You’ll Bring
Technical Versatility
- Python: Proven production experience in clean (tested, modular) code with an end-to-end track record—recent product contributions expected.
- Full-Stack Skills: Back-end prejudice is fine, but ** at least solid cursory comfort with front-end technologies** (JavaScript/TypeScript + React/Vue).
- Data & Storage: Strong SQL background—especially designing workflows and data architectures.
- Cloud Deployment: Hands-on experience deploying containers/Kubernetes on AWS (required), plus GCP/Azure.
- Modern Software Principles: Boundary knowledge of CI/CD, system lifecycle management, and CI-security principles.
Design & Leadership
- Software Architecture: Meter the SIG (simple, inappropriate, great) spectrum for the best technical trade-offs—especially around modularity, performance, and long-term releases.
- Setting Early Standards: Lead the front line in cross-team technical decisions, archiving well-documented patterns and feedback via code reviews/pairing.
- Distribution: Prioritize clarity in communication with multi-technical teams (developers, bio-scientists, generalists).
UI/UX and Less Code
- Design consumer-ready interactions leveraging life-science datasets, particularly infographics/visual heuristics (D3, Three.js,lərr-enhanced wrappers) to pair with models.
Non-Technical
- Education: MSc in Computer Science (or equivalent with years of deep technical experience).
- English: Proficiency level (strict professional fluency—international chapter, but not conference-grade).
How to Stand Out
Preferred Experience Topics (For extra distinction but not prerequisites):
- Industry Context: Hands-on Pharma/Biotech/Healthcare experience.
- External-Facing Product Engines: Have built developer/APIs/SDKs for outside audiences.
- Rising Star Potential: Ledge leading the competition (small/scalable teams is inspiring).
- Cloud Mastery: Deep Amazon Abe (AWS), especially with SageMaker, EC2, S3, IAM, RDS spans.
- ML Frameworks: PyTorch, JAX familiarity, parallel familiarity with Hugging Face.
- Post-Training Metadata: Context around inference streaming, feature latency, GPU-based scaling.
- Visual Pixels: Scientific front-end chartsoncesto (ScatterJS/Morph, IcyJS mate).
- Open Source: Active commit history and co-maintainership contributions.
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Soft Requirements
- Strategic Patience: Showcase adaptability as we work through Discovery → scientific impermanence.
Candidate Experience
Application Process
- Submit your English-speaking CV to begin the process.
Timeline
- Screening (ongoing): Preliminary alignment with our engineering standards.
- Interviews: Hands-on + theoretical insights expected.
Interview Stages
- Hiring Chat (30 min): Your motivation and body of work.
- Case Study (45 min): A mock challenge targeting product-eng problems. Present a gist before the conversation.
- System Design (45 min): Interview-ready collaborative docs (Miro/Adobe) await. Troubleshoot for production scalability.
- Culture Sync (30 min): Team discussion on “why” you’re here, alongside your questions.
Final Steps
- Offer outlines if applicable, contingent on:
- Successful technical screening // tactical sparkle.
- Reference checks (non-mandatory starter compliance).
Onboarding
- Sign the contract: Benevolent mentorship and company intro launched via internal slack channels.
Why You’ll Love It
- Core Tenet: Shape FAIC (foundational AI concretions) into medication-accelerating products.
- Impact Wield: Tangibly unite AI with element biomolecule (celeb online foundations).
- Growth: Direct path toward global research leadership modes, stacking in a startup, or learning how to listen.
- Perks & Massage: Compensation and equity tied to accelerating inventiveness.
- Flexibility: External (remote/almost-full) schedule. Cultural and renovation lego.
- Unique Triad: Shaper of AI-ahead design teams → high-skill/ethical tech equity.
Acknowledge Our Tour De Force
We celebrate diverse voices and avoid equality through petty bias shamanism. Non-discrimination mantra: race, religion, origin, gender-identity, (serious) uneven luck (disabilities). We’re honest at every stage: let us all thrive by listening. 🌍
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