Applied ML Engineer
Indexed description
The Applied ML Engineer builds applied machine learning systems within a Production Platform Engineering pod. This role translates technical direction into working software, including model integrations, data pipelines, retrieval systems, evaluation instrumentation, and service layers. Working within defined execution cycles, the Applied ML Engineer delivers modular, testable systems that can be evaluated, integrated, and extended by downstream teams. The role focuses on implementation and iteration, not architecture ownership, model behavior definition, or system recovery.
Key Responsibilities
Applied ML System Development
- Implement machine learning systems, including model integrations, data pipelines, retrieval systems, evaluation instrumentation, and service layers.
- Translate technical direction into modular, maintainable codebases with clear interfaces.
- Deliver working artifacts at defined milestones, including code, configuration, tests, and documentation.
- Iterate on systems based on evaluation results, domain feedback, and integration requirements.
- Refine performance, usability, and functionality within the scope of the system being built.
- Support rapid development cycles while maintaining code quality and reproducibility.
- Implement evaluation hooks, metrics, and instrumentation defined by the ML Behavior Systems team.
- Ensure systems can be tested against defined benchmarks and quality standards.
- Support debugging and iteration based on evaluation outcomes.
- Build systems using ML Platform & Operations infrastructure for training, inference, and deployment.
- Ensure compatibility with platform services, APIs, and constraints.
- Follow established patterns for system integration and deployment readiness.
- Design outputs as modular components with stable interfaces.
- Include configuration controls, observability hooks, and error handling required for integration.
- Partner with Platform Integration teams to ensure deliverables meet downstream requirements.
- Delivery: Working systems are delivered within defined execution cycles.
- Code quality: Code is modular, readable, and maintainable by downstream teams.
- Evaluation readiness: Systems can be measured and validated against defined standards.
- Integration readiness: Outputs can be adopted without significant rework.
- 4+ years of software engineering experience in backend, systems, or ML-adjacent environments.
- 2+ years hands-on ML implementation.
- Proficient programming skills, particularly in Python, and experience building APIs or services.
- Working knowledge of machine learning systems, including model integration, evaluation, and debugging.
- Experience building end-to-end systems from unclear requirements to working software.
- Ability to operate in dynamic, iterative development environments.
- Experience building ML-enabled systems such as retrieval pipelines, agent workflows, or model-backed services.
- Familiarity with evaluation instrumentation, logging, and tracing in ML systems.
- Experience working with cloud-based infrastructure and distributed systems.
- Contributions to reusable libraries, frameworks, or internal platforms.
- Execution focus: Translates direction into working systems proficiently.
- System implementation: Proficient ability to build across model, data, and service layers.
- Iteration discipline: Improves systems based on feedback and evaluation results.
- Integration awareness: Builds with downstream systems and constraints in mind.
- Collaboration: Works successfully within a pod and across engineering, domain, and integration teams.
Additional Information
Hiring Salary Range: $124,000.00 - 186,000.00.
The hiring salary range for this position applies to New York, California, Colorado, Washington state, and most other geographies. Starting pay for the successful applicant depends on a variety of job-related factors, including but not limited to geographic location, market demands, experience, training, and education. The benefits available for this position include medical, dental, vision, 401(k) plan, life insurance coverage, disability benefits, tuition assistance program and PTO or, if applicable, as otherwise dictated by the appropriate Collective Bargaining Agreement. This position is bonus eligible.
What We Offer:
- Attractive compensation and comprehensive benefits packages. Check out our full list of benefits here: https://www.paramount.com/careers/benefits
- Generous paid time off.
- An exciting and fulfilling opportunity to be part of one of Paramount’s most dynamic teams.
- Opportunities for both on-site and virtual engagement events.
- Unique opportunities to make meaningful connections and build a vibrant community, both inside and outside the workplace.
- Explore life at Paramount: https://www.paramount.com/careers/life-at-paramount
At Paramount, the spirit of inclusion feeds into everything that we do, on-screen and off. From the programming and movies we create to employee benefits/programs and social impact outreach initiatives, we believe that opportunity, access, resources and rewards should be available to and for the benefit of all. Paramount is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, creed, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, and Veteran status.
If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to use or access https://www.paramount.com/careers as a result of your disability. You can request reasonable accommodations by calling 212.846.5500 or by sending an email to [email protected]. Only messages left for this purpose will be returned.
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