Johnson & Johnson is currently seeking a Sr Principal MLOPs Engineer role to join our located in US.

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at https://www.jnj.com/.

For more than 130 years, diversity, equity & inclusion (DEI) has been a part of our cultural fabric at Johnson & Johnson and woven into how we do business every day. Rooted in Our Credo, the values of DEI fuel our pursuit to create a healthier, more equitable world. Our diverse workforce and culture of belonging accelerate innovation to solve the world’s most pressing healthcare challenges.

We know that the success of our business – and our ability to deliver meaningful solutions – depends on how well we understand and meet the diverse needs of the communities we serve. Which is why we foster a culture of inclusion and belonging where all perspectives, abilities and experiences are valued and our people can reach their potential.

At Johnson & Johnson, we all belong.

Johnson & Johnson MedTech Digital (JJMT) is recruiting a Technical Lead – AI/ML (Sr Principal Engineer) to join a strategic team of engineers and applied scientists with a mission to create new innovative solutions for digital surgery. JJMT Digital is passionate about crafting the future of digital surgery by developing software products and solutions for hospitals, clinicians, and patients. These products will deliver a comprehensive digital surgery experience for J&J Med Tech customers and their patients from pre-operative care through post-operative support. This position will lead several ML engineering modules and will have a direct impact on re-defining patient care.

Key Responsibilities:

• Lead strategic execution around ML systems and training infrastructure and deploying traditional models and large language models


• Define execution processes that strive for streamlined engineering development and deployment


• Closely follow the platform roadmap and work on improving delivery of features to serve platform use cases


• Own technical projects from start to finish, contribute to the team’s product roadmap, and be responsible for major technical decisions and tradeoffs. Effectively participate in team’s planning, code reviews and design discussions


• Collaborate with stakeholders to understand data requirements and translate them into technical specifications and data integration solutions.


• Consider the effects of projects across multiple teams and proactively manage risks/conflicts.


• Work together with partner teams and organizations to achieve cross-departmental goals and satisfy broad requirements

Experience and Skills:

Required:

• Minimum 5+ years working on ML systems for training and deploying complex ML models and MLOps pipelines


• Experience working on the scaling challenges associated with building models and/or other data pipelines


• Experience with at least one cloud platforms, such as AWS, Azure, or GCP, and their respective data integration services.


• Significant experience in object-oriented programing and strong proficiency in programming languages, especially in Python, but also SQL and/or Java.


• Experience with data modeling, pipeline development and analysis within data science/data engineering platforms such as Databricks, Azure ML, C3.ai, Snowflake.


• Attention to detail and a passion for truth


• A track record of efficiently solving complex problems collaboratively on larger teams


• Startup mentality - openness to dealing with unknown unknowns and wearing many hats


• Strong expertise in writing production quality code and setting standards for code quality across engineering teams


• Experience in driving technical strategy and vision for engineering teams and organizations


• In-depth understanding of software development lifecycle (SDLC) and best practices - CI/CD, coding, debugging, optimization, testing, integration and deployment

Nice to have:

• Familiarity with healthcare data standards and protocols, including HL7, DICOM, and FHIR.


• Understanding of data governance principles and data privacy regulations, such as HIPAA and HITRUST®