Senior Machine Learning / MLOps Engineer

Location: Dearborn, Michigan, United States; hybrid work

Company

hirify.global provides technology services and collaborates with clients on software, data, and emerging technology initiatives.

What you will do

• Build scalable cloud-based ML data pipelines for large volumes of connected vehicle data using batch and streaming ingestion.
• Develop analytical data products and monitor data quality, model performance, and AI solution reliability.
• Optimize data and ML solutions for performance, security, reliability, and cost-effectiveness.
• Maintain data platform infrastructure with Terraform and enhance DevOps capabilities through CI/CD, TDD, and continuous deployment.
• Implement enterprise data governance, data mapping, data lineage, and documented information flows.
• Provide production support, troubleshoot pipeline and product issues, collaborate with stakeholders, and mentor junior team members.

Requirements

• Bachelor’s degree in computer science, software engineering, information systems, data engineering, or a related field, plus 6+ years of experience; or a master’s degree with 4 years of experience.
• At least 4 years of professional experience in data engineering, data product development, and software product launches.
• At least 4 years of experience with three or more of Java, Python, Spark, Scala, and SQL.
• At least 3 years of cloud data or software engineering experience building production batch and streaming pipelines.
• Deep knowledge of ML/AI Ops on Google Cloud Platform, machine learning, MLOps, Python, TensorFlow, and data governance.
• Experience with BigQuery or comparable cloud data warehouses, Airflow, Kafka or GCP Pub/Sub, relational databases, REST APIs, microservices, GitHub, Terraform, Docker, and CI/CD tools.

Nice to have

• Ph.D. or foreign equivalent degree in a related field.
• Experience with ML model development, open-source projects, cloud infrastructure architecture, migrations, and upgrades.
• GCP professional certifications and knowledge of telematics.
• Experience with data modeling, data mining, database design, and pipeline automation.

Culture & Benefits

• Collaboration with technical experts, clients, and cross-functional teams.
• Opportunities for long-term career growth and work with emerging technologies.
• Benefits may include medical, dental, and vision coverage, paid time off, paid holidays, 401(k) matching, life and disability insurance, professional development, and wellness programs.
• Inclusive workplace focused on diversity, dignity, and respect.