DESCRIPTIONThe Associate Engineer is a developing individual contributor who delivers reliable, well-scoped engineering work within established patterns. You will help build data pipelines, ML workflow components, and platform features that support production-ready AI/ML solutions. You will build technical proficiency, contribute consistently against team commitments, and work within proven architecture patterns with guidance from senior engineers after initial alignment. This role is well suited for early-career engineers who are ready to take on real ownership while building toward increasingly independent delivery. The ideal candidate is dependable, curious, and eager to grow.
KEY RESPONSIBILITIES Technical Delivery
- Implement data pipelines, ML workflow components, and platform features following established architecture patterns and coding standards.
- Write readable, maintainable, testable code with limited guidance after initial design alignment with senior engineers.
- Deliver well-scoped work reliably and on schedule; understand how your work fits into the larger solution.
Problem Solving
- Write and maintain tests for your work; ensure changes are tested before deployment.
- Troubleshoot issues within your assigned pipelines and features with minimal guidance; identify root causes and propose solutions.
- Navigate the codebase and data designs with growing independence after initial orientation.
Collaboration & Growth
- Contribute input to team scoping and design exercises; share observations that improve how the team approaches recurring problems.
- Explain your work clearly to teammates, including what you built, why, and any trade-offs.
- Demonstrate awareness of the business context for your work and how it connects to the team's broader goals.
- Take ownership of your development; actively seek feedback and apply it to strengthen your technical and professional skills.
QUALIFICATIONS Education
- BA/BS required (quantitative or engineering discipline preferred).
Experience
- 0-2 years of experience in data engineering, software engineering, ML engineering, or a related field; relevant advanced degrees contribute to required years of experience.
Technical Skills
- Proficiency in Python and SQL; familiarity with data pipeline development and common processing patterns.
- Working knowledge of version control (Git), testing practices, code review, and documentation.
- Exposure to cloud environments (AWS, Azure, or Databricks); willingness to develop deeper platform proficiency.
- Familiarity with ML concepts and workflows (model training, feature engineering, data preparation); MLOps experience a plus.
Competencies
- Works effectively within team guidelines and standards.
- Builds positive working relationships with teammates and cross-functional partners.
- Reliable: delivers commitments and communicates proactively when blockers arise.
- Demonstrates curiosity and commitment to growing technical and professional skills.
If you come across a role that intrigues you but doesn't perfectly line up with your resume, we encourage you to apply anyway. You could be one step away from work that will transform your life and career.
Compensation Overview:Princeton - NJ - US: $81,260 - $98,468
The starting compensation range(s) for this role are listed above for a full-time employee (FTE) basis. Additional incentive cash and stock opportunities (based on eligibility) may be available. The starting pay rate takes into account characteristics of the job, such as required skills, where the job is performed, the employee's work schedule, job-related knowledge, and experience. Final, individual compensation will be decided based on demonstrated experience.
Eligibility for specific benefits listed on our careers site may vary based on the job and location. For more on benefits, please visit https://careers.bms.com/life-at-bms/.
Benefit offerings are subject to the terms and conditions of the applicable plans in effect at the time and may require enrollment. Our benefits include:
- Health Coverage: Medical, pharmacy, dental, and vision care.
- Wellbeing Support: Programs such as BMS Well-Being Account, BMS Living Life Better, and Employee Assistance Programs (EAP).
- Financial Well-being and Protection: 401(k) plan, short- and long-term disability, life insurance, accident insurance, supplemental health insurance, business travel protection, personal liability protection, identity theft benefit, legal support, and survivor support.
Work-life benefits include:Paid Time Off
- US Exempt Employees: flexible time off (unlimited, with manager approval, 11 paid national holidays (not applicable to employees in Phoenix, AZ, Puerto Rico or Rayzebio employees)
- Phoenix, AZ, Puerto Rico and Rayzebio Exempt, Non-Exempt, Hourly Employees: 160 hours annual paid vacation for new hires with manager approval, 11 national holidays, and 3 optional holidays
Based on eligibility*, additional time off for employees may include unlimited paid sick time, up to 2 paid volunteer days per year, summer hours flexibility, leaves of absence for medical, personal, parental, caregiver, bereavement, and military needs and an annual Global Shutdown between Christmas and New Years Day.
All global employees full and part-time who are actively employed at and paid directly by BMS at the end of the calendar year are eligible to take advantage of the Global Shutdown.
*Eligibility Disclosure: The summer hours program is for United States (U.S.) office-based employees due to the unique nature of their work. Summer hours are generally not available for field sales and manufacturing operations and may also be limited for the capability centers. Employees in remote-by-design or lab-based roles may be eligible for summer hours, depending on the nature of their work, and should discuss eligibility with their manager. Employees covered under a collective bargaining agreement should consult that document to determine if they are eligible. Contractors, leased workers and other service providers are not eligible to participate in the program.
R1603317 : Associate Engineer, Analytical AI Engineering
