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

TechniPros, LLC

Seattle, WA, United States

about 1 month ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

8 years minimum

Working hours

Regular working hours

Job source

www.careerjet.com

Tech stack

Amazon Web Services Data Analysis Big Data Cloud Computing Software Quality Information Systems Continuous Integration Data Discovery Distributed Systems Machine Learning Object Detection Recommender Systems

+15 more

Software Deployment Workflow Management Systems Datadog Data Logging Feature Engineering Apache Spark Deep Learning Backend Information Technology Apache Kafka Machine Learning Operations Amazon Simple Queue Service (SQS) 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