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At Boston Bioprocess Inc., our mission is to revolutionize biotech manufacturing through the power of AI. We are an AI-native SaaS company that builds cutting-edge software to help clients track and optimize their research, development, and manufacturing operations. We believe success is built on a foundation of technical excellence, clear communication, empathy, and a proactive, can-do attitude for solving complex challenges.
We are looking for an experienced and passionate AI-native Software Engineer to join our data science team. This is fundamentally a software engineering role with a strong machine learning focus—we need someone who designs, builds, and operates production systems, and who specializes in the software stack for building and scaling ML models.
You will take the lead in building the engineering backbone behind our AI-driven bioprocess platform, turning early-stage models into dependable services that our clients and scientists rely on every day. This involves building and operating our portfolio of ML-powered applications, backend services, REST APIs, data pipelines, scheduled jobs, and the dashboards that sit on top of them. Our state-of-the-art ML tools are regularly re-trained on fresh laboratory data to directly shape the decisions our scientists and clients make every week. Your job will be to make sure these systems run reliably, scale gracefully, and evolve cleanly as the science and our client base grow.
Beyond these core projects, you will collaborate closely with our data scientists, backend engineers, and wet-lab scientists to build Agentic AI systems, manage data pipelines, prepare datasets for machine learning models, and create insightful dashboards to optimize everything from laboratory experiments to commercial-scale manufacturing.
Key Responsibilities & Workflow
Production ML: Design, develop, and own the production services that power our predictive, optimization, and generative AI applications using FastAPI, PyTorch, and AWS.
MLOps & Infrastructure: Own deployment, retraining workflows, and establish best practices for versioning, CI/CD, observability, and drift monitoring. Be judicious in balancing supporting immediate needs with long-term infrastructure requirements.
Engineering Rigor: Bring modular architecture, typed interfaces, and robust testing to early-stage ML code. Write clean, maintainable, and efficient code, taking ownership of the quality and performance of the ML systems you build.
Backend & Data Connectivity: Create robust REST APIs, ETL pipelines, and human-in-the-loop feedback systems.
Cross-Functional Collaboration: Work closely with data scientists and wet-lab scientists to translate scientific requirements into production constraints.
Agile & AI-Assisted Development: Actively integrate AI-powered tools into your daily workflow to optimize and speed up tasks such as coding, refactoring, testing, and documentation. Effectively use Agile practices to plan and track your work.
Requirements
Education & Experience: Master’s degree in Computer Science, Engineering, or a related field from a reputed US/European/APAC University with 2+ years of proven experience as a Full-Stack Developer (or similar role), OR a Bachelor’s degree from a Tier 1 Indian University with 5+ years of experience in a related field.
Frontend Expertise: Deep expertise in building complex, UI-heavy, and responsive web applications using React.js, Next.js, Svelte, etc.
Backend Knowledge: Strong knowledge of Python-based back-end languages such as FastAPI, Django, or similar.
Data & Databases: Experience with databases like MySQL, PostgreSQL, or similar, including schema design for experimental or scientific data.
ML in Production: Hands-on experience integrating ML frameworks (PyTorch, Jax, Tensorflow, or similar) into production software, with a clear understanding of how inference, batching, and model lifecycle behave under real load.
Cloud & DevOps: Proven experience deploying and maintaining services and ML models on cloud platforms—AWS (SageMaker, ECS, Lambda), GCP, or similar—alongside proven experience with DevOps practices and CI/CD pipelines.
Core Soft Skills: Strong communication, excellent problem-solving skills and attention to detail.
Nice-to-Haves
Experience building LLM-powered applications (prompt engineering, evaluation, caching, agentic workflows).
Experience with Bayesian methods, optimization under uncertainty, or recommender systems.
Exposure to laboratory informatics systems (LIMS) or Manufacturing Execution Systems (MES), or similar.
The Ideal Candidate & What We Offer
Culture Fit: You thrive in a small, agile team with minimal bureaucracy and a fast-paced culture. You are a motivated collaborator and a bridge-builder who sees the gap between early-stage model code and production systems as the interesting part of the job, not the boring part. You have opinions about where that line should be drawn and the judgment to know when to cross it.
Compensation: Salary of $15K USD to $30K USD depending on skills and experience.
Benefits: Complete benefits package including health, life, vision, and dental insurance, plus four weeks of paid vacation.
