Machine Learning Engineer

Location: California

The
** Machine Learning Engineer
** designs, builds, and product ionizes end-to-end AI/ML systems that measurably improve business outcomes. This role owns the technical lifecycle of models from data and features through deployment, monitoring, and continuous improvement. You will ship reliable, well-tested services that move KPIs in areas such as ranking, recommendations, yield optimization, fraud detection, and intelligent routing, while also contributing to emerging AI initiatives including LLMs and agentic systems.
**** Qualifications** -*
* **** Detailed

Job Duties:

****(
* typical monthly, weekly, daily tasks which support the primary objectives*)
* Deploy models via RESTful APIs, containerized services, or scheduled jobs, with appropriate reliability safeguards.
* Work with software and data engineering to integrate models into production systems.
* Ensure deployments are reproducible, versioned, and compatible with CI/CD practices.
* Collaborate with stakeholders to define success metrics, communicate progress, and manage risks transparently.
* Translate business requirements into technical ML deliverables.
* Align model design with product roadmaps and engineering constraints.
***
* NOTE:

** Depending on location or product team, the role may emphasize one of the following without changing level or title:
****** The MUST Haves:**** (
* ex: job cannot be done without these skills, education, experience, certifications, licenses*)
* Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field, or equivalent experience.
* 3+ years of hands-on ML engineering experience delivering models to production.
* Strong Python and working SQL; solid software engineering fundamentals including testing, modular design, and version control.
* Experience with classical ML such as tree-based models, linear/logistic models, and model evaluation.
* Working knowledge of a deep learning framework such as PyTorch or Tensor Flow.
* Experience building data and feature pipelines for training and inference.
* Experience deploying models via APIs, microservices, or batch/streaming systems.
* Demonstrated ability to improve models through iteration, tuning, or redesign.
* Clear written and verbal communication; ability to partner effectively across teams.
**** The Nice to Haves:**** (ex:
* preferred additional skills, education, experience, certifications, licenses*)
* Master’s degree or PhD in AI, Machine Learning, or a quantitative field.
* Experience with ranking or recommendation systems at scale.
* Experience with distributed computing frameworks such as Spark, Ray, or Flink.
* Cloud experience on AWS, Azure, or GCP plus MLOps tooling such as MLflow or model registries.
* Familiarity with Docker/Kubernetes.
* Exposure to LLM tooling including Hugging Face, embeddings, RAG, or agent frameworks.
* Additional languages such as Java, Scala, or Rust.

Prodege offers a comprehensive benefits package to US Full-time employees including medical, dental, vision, STD, LTD and basic life insurance. Employees receive flexible PTO, as well as paid sick leave prorated based on hire date. US Employees have eight paid holidays throughout the calendar year. Employees receive an option to purchase shares of Company stock commensurate with their position, which vests over four years.

Employers will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of
** FCIHO.*
* #J-18808-Ljbffr