Bioinformatics Software Engineer II, Integrated Genomics at Memorial Sloan Kettering Cancer Center

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

10 Apr, 26

Salary

161000.0

Posted On

10 Jan, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Bioinformatics, Software Engineering, Genomics, Full-Stack Development, React, JavaScript, TypeScript, Node.js, Python, Java, REST APIs, GraphQL, SQL, Linux, AI Development Tools, Collaboration, Communication

Industry

Hospitals and Health Care

Description

About Us: The people of Memorial Sloan Kettering Cancer Center (MSK) are united by a singular mission: ending cancer for life. Our specialized care teams provide personalized, compassionate, expert care to patients of all ages. Informed by basic research done at our Sloan Kettering Institute, scientists across MSK collaborate to conduct innovative translational and clinical research that is driving a revolution in our understanding of cancer as a disease and improving the ability to prevent, diagnose, and treat it. MSK is dedicated to training the next generation of scientists and clinicians, who go on to pursue our mission at MSK and around the globe. Exciting Opportunity at MSK: Memorial Sloan Kettering’s Integrated Genomics Operation (IGO) is seeking a Software Engineer to join our Data and Software Engineering Team! In this role, you will help design, build, and support platforms that capture, organize, and deliver petabytes of genomic data, powering breakthrough cancer research across MSK. You’ll work closely with and collaborate with the Senior Software Engineer leading the team, gaining mentorship while contributing to production-grade systems used by researchers and clinicians. This is a great opportunity for an emerging engineer who wants hands-on experience building real-world systems in a mission-driven, research-focused environment—while learning to leverage modern AI development tools in a rigorous engineering setting. Role Overview: Collaborate with a small team of full-stack engineers to design, develop, and maintain software supporting genomic workflows. Implement new features and fixes across key platforms, including our LIMS, data‑archiving pipelines, and internal delivery APIs. Build intuitive user interfaces using React, JavaScript, and TypeScript, and contribute to back‑end services in Node.js, Python, and/or Java. Write clean, maintainable code and contribute to unit, integration, and end-to-end testing. Participate in design discussions, code reviews, and GitHub-based development workflows. Monitor and troubleshoot systems in a data-intensive environment, helping improve performance and reliability. Work with wet‑lab scientists to translate their needs into technical solutions. Use AI-assisted development tools (e.g., code-completion and code-review assistants) to increase development speed, code quality, and test coverage while maintaining strong engineering standards Key Qualifications: Bachelor’s degree in Computer Science, Bioinformatics, or a related technical field; or 2–4 years of relevant experience. Master's Degree preferred. 2+ years of experience building software through professional work, internships, research, or substantial personal/open‑source projects. Familiarity with HTML, CSS, JavaScript/TypeScript; experience with React preferred. Exposure to back-end development using Java, Python, or Node.js. Understanding of REST or GraphQL APIs. Basic knowledge of SQL and relational databases (e.g., MySQL, PostgreSQL). Comfortable working in a Linux environment and using command-line tools. Interest in genomics, bioinformatics, or scientific/healthcare data (preferred but not required). Experience with AI coding assistants—or interest in learning them effectively Core Skills: Excellent communication skills with both technical and non‑technical partners. Curiosity and a growth‑oriented attitude; eager to learn from mentorship. Collaborative approach to collaboration, including pairing and code review. Ability to incorporate AI-assisted tools thoughtfully while maintaining independent problem-solving skills. Customer-focused orientation—motivated to improve scientist and analyst workflows. Organized, reliable, and able to spearhead work in a fast-paced research environment. Additional Information: Location: 1250 1st Avenue, New York, NY (Schwartz) Schedule: On-site 4 days per week, 37.5 hours a week Reporting to: Data & Software Engineering Team Lead Helpful Links: Compensation Philosophy Benefits #IND #LI-POST Pay Range: $100,600.00 - $161,000.00 FSLA Status: Exempt Closing: At MSK, we believe in fair, competitive pay that reflects your job, experience, and skills. MSK is an equal opportunity and affirmative action employer committed to diversity and inclusion in all aspects of recruiting and employment. All qualified individuals are encouraged to apply and will receive consideration without regard to race, color, gender, gender identity or expression, sexual orientation, national origin, age, religion, creed, disability, veteran status or any other factor which cannot lawfully be used as a basis for an employment decision. Federal law requires employers to provide reasonable accommodation to qualified individuals with disabilities. Please tell us if you require a reasonable accommodation to apply for a job or to perform your job. Examples of reasonable accommodation include making a change to the application process or work procedures, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment. Our multi-disciplinary teams work together to provide exceptional patient care, develop innovative research, and deliver outstanding educational programs. Learn More The people of MSK make this an incredible place to work, grow and make a difference. Discover what makes us unique

Responsibilities

The role involves collaborating with a team to design, develop, and maintain software for genomic workflows. Responsibilities include implementing features, building user interfaces, and monitoring systems in a data-intensive environment.