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SeniorFull-timePythonAWSKubernetesDockerTerraformMachine LearningData ScienceTensorFlowPyTorchGit
Salary Range
$70,000 - $87,000 /year
About the Role
We are looking for a Machine Learning Engineer to join our team at TrueML, a mission-driven financial software company. This role focuses on building and scaling mission-critical ML pipelines and data platforms that serve millions of customers daily.
Key Responsibilities
- →Architect the ML Ecosystem: Own the end-to-end lifecycle of our ML infrastructure, designing a scalable, modern environment that enables models to thrive in production.
- →Productionize Innovation: Partner closely with our Data Science team to take complex algorithms from the 'lab' to the 'real-world', building the high-performance pipelines required to scale them.
- →Engineer Feature Intelligence: Design and maintain both offline and online feature stores, ensuring our models have the high-quality data they need for instant decision-making.
- →Scale the Data Platform: Collaborate with Data Engineers to evolve our data lake and ETL architectures, ensuring our data platform remains robust and future-proof.
- →Ensure System Health: Lead the monitoring and observability strategy for all production models, ensuring reliability and performance through proactive maintenance.
- →Shape Technical Strategy: Act as a key stakeholder in architectural decisions, helping the broader team define the strategy for our data products and event-driven architectures.
Requirements
- ✓A Proven Builder: You have 5+ years of hands-on experience in ML Engineering, with a significant focus (3+ years) on the data engineering side of the house.
- ✓Cloud Native: You are an expert in the AWS ecosystem (Sagemaker, DynamoDB) and thrive using Infrastructure as Code tools like Terraform, CDK, or CloudFormation.
- ✓Automation Minded: You have a deep understanding of containerization and orchestration, specially using Docker and Kubernetes to deploy scalable workloads.
- ✓Technical Polymath: You possess a deep understanding of database systems, ETL architecture, and advance SQL, alongside mastery of Python and frameworks like TensorFlow, PyTorch, or Scikit-learn.
- ✓Strategic Collaborator: You excel at working across functional lines - Translating Data Science needs into engineering requirements and mentoring others on best practices.
- ✓Big Data Enthusiast: You ideally have experience with Snowflake, Databricks, or streaming technologies like Kafka to handle event-based data at scale.
Benefits
- ★Unlimited PTO
- ★Medical benefit contributions in congruence with local laws and type of employment agreement
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