The Best Biotechnology Jobs

Tracked at 10k top companies

(Updated 2 hours ago)

Explore a handpicked list of biotech jobs hiring in 2025. Simplify has handpicked opportunities covering data science, software engineering, bioinformatics, machine learning, and biostatistics at top health tech startups, mission-driven biotech companies, and global pharmaceutical firms.

You'll find jobs for entry-level graduates (2024 and 2025), mid-level professionals, and experienced engineers. Whether you're a biotechnology major, a Python or R programmer, a data scientist working on genomics, or a software engineer building tools for AI in healthcare, this list includes remote, hybrid, and in-person jobs in biotech hubs like San Francisco, Boston, New York, and San Diego.

Search across biotechnology vacancies at companies ranging from VC-backed startups (including Sequoia and a16z portfolio companies) to public health tech firms and Series A-C therapeutics startups. These are high-impact roles that combine engineering, analytics, and biology, designed for those passionate about transforming healthcare through technology.

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Learn just enough domain context to build useful tools. Start with basic genomics (e.g. what is FASTQ, CRISPR, or RNA-seq). Explore public bio datasets (like TCGA or UniProt) and try building tools around them. Biotech companies want engineers who can work with scientists, even if they’re not scientists themselves.

Python dominates, especially with libraries like Pandas, NumPy, Biopython, and scikit-learn. For backend roles, Flask, FastAPI, and PostgreSQL are common. Data engineers might use dbt or Snowflake. Some teams use R, especially in bioinformatics-heavy roles. Experience with AWS or Nextflow is a bonus in computational biology roles.

Biotech engineering teams often support research, not products. That means less focus on scale and more on flexibility, reproducibility, and scientific data pipelines. You might be writing data cleaning scripts one week and debugging cloud pipelines the next. Expect blurry specs and close collaboration with scientists.

No, but you’ll need to show strong modeling skills and the ability to pick up biological context. Many teams hire generalist data scientists who can wrangle experimental data and communicate findings clearly. If you’ve worked with noisy, time-series, or high-dimensional data, that’s a strong signal, even if it wasn’t in a biology setting.

Ask who the end users of your work will be (scientists, patients, internal ops?), how engineering collaborates with wet lab teams, and what kind of data infrastructure already exists. If it’s a research-heavy company, ask how software is prioritized, some teams treat engineers as support rather than partners.

Contribute to open bioinformatics tools, take a free course like MIT’s intro to computational biology, or read biotech engineering blogs (like Benchling or Recursion). Mention specific companies or technologies you’re interested in (like CRISPR, RNA therapeutics, or spatial transcriptomics) in your cover email, it helps hiring managers take your pivot seriously.