- Architect, develop, and deploy end-to-end AI/ML systems addressing key QE workflows (e.g., bug prediction, app confidence scoring for incremental releases, flaky test detection, intelligent test prioritization, anomaly detection).
- Perform LLM fine-tuning (full-model, LoRA/QLoRA, instruction tuning) and determine when fine-tuning is appropriate vs. RAG-only or hybrid approaches.
- Develop model evaluation frameworks ensuring accuracy, robustness, and safe behavior over time.
- Identify and prioritize opportunities to integrate AI automation across test strategy, execution, triage, and release decisioning.
- Integrate AI into CI/CD pipelines for dynamic risk-based testing, anomaly detection, and intelligent quality gates.
- Build solutions that analyze logs, traces, telemetry, and user signals to detect emerging quality risks.
- Leverage Google Cloud Vertex AI to build scalable, production-grade AI systems, including:
- Integrate Vertex AI with GCP services (BigQuery, Cloud Run, GKE, Pub/Sub) for full production deployment.
- Lead architectural decisions on LLM system design, MLOps, data pipelines, and monitoring strategies.
- Mentor engineers on applied ML, modern AI development, prompt engineering, and RAG-vs-fine-tuning tradeoffs.
- Partner in the creation of engineering standards for model governance, safety, code quality, and scalable AI development.
- Collaborate with peers in GQE as well as DevOps, SRE and Infosec teams to translate quality challenges into high-value AI solutions that accelerate testing.
- Work closely with Data Engineering to ensure training data quality, governance, privacy, and compliance.
- Clearly communicate complex concepts to a variety of audiences including executives, engineers, and non-technical stakeholders.
- 7+ years of experience in machine learning engineering, software engineering, or applied AI.
- Strong expertise in Java, Python, PyTorch/TensorFlow, and modern LLM tooling.
- Strong hands-on experience with LLM fine-tuning, including:
- Expertise selecting between RAG vs. fine-tuning vs. hybrid approaches based on data characteristics, quality needs, and business constraints.
- Production experience with Google Cloud Vertex AI, including training, tuning, pipelines, Vector Search, and real-time model deployment.
- Solid understanding of quality engineering tools, automation frameworks (Selenium, Appium, Playwright, pytest, JUnit, TestNG), and CI/CD systems.
- Experience with MLOps platforms (MLflow, Kubeflow, SageMaker, Databricks) and cloud platforms (Azure, AWS, or GCP).
- Experience building AI systems specifically for engineering productivity or quality engineering.
- Experience mentoring engineers or serving as a technical lead on cross-functional AI projects.
- Architectural judgment - mastery of when to apply RAG, fine-tuning, hybrid retrieval models, or classical ML.
- Innovation mindset - constantly identifying opportunities to improve velocity, quality, and automation with AI.
- Systems thinking - ability to model complex SDLC and QE workflows.
- Strong communication and the ability to drive consensus among stakeholders.
- Ownership - ability to drive initiatives end-to-end with autonomy.
- Reduction in escaped defects and increased early bug detection.
- Faster release cycles through intelligent, AI-driven testing strategies.
- Improved developer and tester productivity via AI-powered tooling.
- Successful deployment and adoption of enterprise-grade AI systems across the org.
Paramount+, a direct-to-consumer digital subscription video on-demand and live streaming service from Paramount Global, combines live sports, breaking news, and a mountain of entertainment. The premium streaming service features an expansive library of original series, hit shows and popular movies across every genre from world-renowned brands and production studios, including BET, CBS, Comedy Central, MTV, Nickelodeon, Paramount Pictures and the Smithsonian Channel.
The service is also the streaming home to unmatched sports programming, including every CBS Sports event, from golf to football to basketball and more, plus exclusive streaming rights for major sports properties, including some of the world's biggest and most popular soccer leagues. Paramount+ also enables subscribers to stream local CBS stations live across the U.S. in addition to the ability to stream Paramount Streaming's other live channels: CBSN for 24/7 news, CBS Sports HQ for sports news and analysis, and ET Live for entertainment coverage.
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.
- Attractive compensation and comprehensive benefits packages. Check out our full list of benefits here:https://www.paramount.com/careers/benefits