Machine Learning Platform Engineer

Location: Solana Beach, California - Remote
Category: Technology
Employment Type: Direct Hire
Job ID: 5345
Date Posted: 09/20/2022

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About the Opportunity:

Our client is looking for  Machine Learning Platform Engineer who will be responsible to operationalize data science models into production via the development, monitoring, and maintenance of scalable, generalizable, hardened machine learning systems. Collaborate with data scientists and fellow engineers to lead the design, implementation, and continuous improvement of our machine learning software architecture to streamline the process of developing and deploying ML models to production. Collaborate with data engineering to establish and maintain data consistency across production and research environments, and is fixated on productivity and efficiency in all aspects of research and development.


  • Reduce time to launch a completed ML model in production to < 1 month via the adoption and development of shared frameworks.
  • Work towards a continuous delivery framework for model deployment with support for experimentation (e.g. A/B testing, blue-green/canary deployment, and monitoring)
  • Continuously monitor and optimize latency on model inference requests with increasing volume
  • Maintain parity between data handling in production and research code bases with minimal code duplication
  • Streamline model development through introducing automation throughout all aspects of the data science workflow, (e.g. EDA, training, parameter tuning, and drift detection)
  • Continuously improve reliability, scalability, security, and cost-effectiveness of ML infrastructure system
  • Take part in the interviewing and consideration of potential new team members
  • Provide guidance and technical mentorship to new team members


  • Masters or PhD in Computer Science, Statistics, Data Science, or related discipline
  • 3 – 5+ years industrial experience working on data science projects
  • Mastery of Python and common DS libraries and frameworks (e.g. Scikit-learn, xgBoost, Tensorflow)
  • Experience with platform infrastructure engineering and/or DevOps is highly desirable
  • Knowledge of operational and memory limitations of machine learning algorithms
  • Experience with common GCP products (e.g. GKE, Load Balancing, Storage, Pub/Sub, IAM, VPC, KMS) or other cloud providers’ equivalents
  • Experience with observability and monitoring tools
  • Mastery of common database query languages and technologies (SQL / Postgres required, Snowflake, non-relational query languages optional)
  • Experience building an end-to-end ML workflow (e.g. on top of Kubeflow, Airflow, MLFlow)
  • Ability to evaluate tradeoffs between competing / complementary 3rd-party ML services and frameworks
  • Ability to design scale-appropriate systems without engaging in overengineering / premature performance optimizations
  • Ability to collaborate and communicate effectively with data scientists and fellow engineers to gather and refine requirements
  • Ability to champion engineering projects independently (i.e. working cross-functionally on a team, but without others with a shared skillset)

About Sayva: Sayva Solutions is an accounting, finance, and technology professional services firm whose focus is on long term relationships created through teamwork and doing what is in the best interest of others. By working with Sayva to identify your next career move, you will get the benefit of working with an experienced team who not only has a strong network of trusted clients, but expertise in the markets, and functions, we serve. We can provide insight on what your market value is, what companies have to offer, and what opportunities align best with your professional and personal goals. We are your trusted advisor throughout your search process and can help ensure you are prepared for interviews, have the information to make the best decisions, and receive a strong offer to land you that perfect job. Making a career move is not easy and can be stressful; Sayva can be your partner in making the process smooth, transparent, and rewarding.