Senior Machine Learning Engineer

Job title: Senior Machine Learning Engineer
Contract type: Full-time
Location: Los Angeles
Industry: Technology
Remote: No
Reference: 424730
Contact name: Lizzette Khodak
Job Published: January 01, 1970

Job description

Our client, a start-up in the retail technology space, is looking for a Senior Machine Learning Engineer to join their team. 

Senior Machine Learning Engineer Responsibilities;
  • Engineering a state of the art Machine Learning software platform
  • Combine strong software engineering principles with machine learning to build scalable, reproducible and easy-to-use end-to-end machine learning workflows for advanced deep learning problems
  • Build backend infrastructure to perform scalable training, evaluation, and inference in the cloud and client-side infrastructure to perform efficient inference on mobile devices
  • Build comprehensive data management systems for scalable data collection, labeling, processing, and evaluation
  • Aid in data ingestion, model training, deployment and monitoring
  • Distribute model training and pipelines on GPU environments.
  • Working closely with experts in Computer Vision to deliver final products
  • Create monitoring solutions that allow effective system accuracy, performance and enable troubleshooting of production ML models
  • Identify gaps and evaluate relevant tools and technologies as needed to improve processes and systems, leveraging open-source and cloud computing technologies to build effective solutions.
  • Collaborate with data scientists, data engineers, product teams, and other key stakeholders and drive ML platform projects from conception to production.
  • Identify performance bottlenecks and optimize different aspects of technology pipelines on CPU and/or GPU.
  • Do ML model conversion to platform specific inferencing frameworks such as CoreML, WinML, ONNX, etc.
Senior Machine Learning Engineer Qualifications:
  • Bachelor's degree in a technical field such as CS, EE, Physics, Math or a related field
  • Familiarity with Machine Learning tools and frameworks 3+ years experience in machine learning engineering
  • Familiarity with cloud services, large datasets and data visualization tools
  • Proven ability to design, implement and operate large projects at scale
  • Strong ability in problem solving and driving for results
Preferred Qualifications
  • Experience in exporting ONNX models
  • Experience in managing and monitoring NVIDIA Triton Inference Serving
  • Experience with KServe
  • Experience with ML tools and IDEs like Sagemaker,Colab pro and Cloud Platforms (AWS, GCP, Azure), services MLperf
  • Experience with any machine/deep learning frameworks like Tensorflow, PyTorch,
  • Strong experience in large scale distributed systems, Data Engineering, MLOps, Machine Learning and Data Science areas Experience with building and deploying ML pipelines in a production environment at scale
  • Good knowledge of AWS, Python, Spark, Airflow, K8s, Docker, Terraform, etc to build pipelines Must have working experience to MLOps tools such as KubeFlow, MLFlow, Metaflow, or Sagemaker
  • Strong understanding of containerization (Docker) and container-orchestration systems like Kubernetes; experience with orchestration tools such as Airflow Experience with stream processing technology Kafka, Spark, Samza, Flink, etc.
  • Working experience and good knowledge of CI / CD tools and best practices
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