Senior Machine Learning Engineer - Seattle,WA,Portland,OR,Boise,ID,Missoula,MT,Farmington,NM

TechniPros, LLC
Seattle, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Seattle, United States of America

Tech stack

Amazon Web Services (AWS)
Data analysis
Big Data
Cloud Computing
Software Quality
Information Systems
Continuous Integration
Data Discovery
Distributed Systems
Machine Learning
Object Detection
Recommender Systems
Software Deployment
Workflow Management Systems
Datadog
Data Logging
Feature Engineering
Spark
Deep Learning
Backend
Information Technology
Kafka
Machine Learning Operations
Amazon Web Services (AWS)
Data Pipelines
Databricks
Microservices

Job description

  • Own complex technical initiatives end-to-end, from technical design through production deployment and operational excellence
  • Design and develop infrastructure supporting the full cycle of machine learning, including data pipelines and workflow orchestration, data discovery and quality tools, and feature libraries
  • Drive data and ML-driven solutions for diverse engineering use cases such as recommendation systems, object detection, autogenerated tagging solutions, RAGs
  • Partner with product, editorial, and engineering stakeholders to translate business requirements into robust technical solutions
  • Strategically prioritize initiatives and technical workstreams to deliver the highest-impact and most time-sensitive outcomes, while proactively identifying, communicating, and mitigating risks to ensure successful execution
  • Champion engineering best practices across code quality, testing, CI/CD, observability, and incident response
  • Mentor and coach engineers, fostering a culture of ownership, collaboration, and continuous improvement
  • Contribute to technical documentation and promote knowledge sharing across teams

Requirements

  • Bachelor degree in Computer Science, Information Systems, Statistics, Math, or comparable field of study, and/or equivalent work experience
  • 8+ years of experience building and operating ML engineering systems in production environments
  • Expertise in data science, deep learning algorithms, or statistical methods to solve real-world engineering problems
  • Comfortable operating at all levels of the predictive stack, including data collection, data analysis, feature engineering, batch training and low-latency online serving
  • Experience designing and developing backend microservices for large-scale distributed systems using REST
  • Experience with cloud infrastructure, preferably AWS (Step Functions, Lambda, Glue, SQS, SNS, Personalize)
  • Familiarity with developing and deploying Spark and ML pipelines
  • Hands-on experience with big data technologies such as Databricks, Kinesis, Kafka
  • Proven leadership, coaching, and mentoring skills, with the ability to inspire and empower a team towards achieving business goals
  • Experience with observability tools for metrics, logging, and monitoring such as Datadog
  • Experience working in Agile/Scrum development environments
  • Excellent communication skills and a commitment to collaboration in a fast-paced, guest-focused environment

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