Note: The job is a remote job and is open to candidates in USA. Dice is seeking a Senior Machine Learning Engineer to lead complex technical initiatives and drive data-driven solutions. The role involves designing and developing machine learning infrastructure and collaborating with various stakeholders to translate business needs into effective technical solutions.
Responsibilities
- 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
Skills
- 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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