CLARA Analytics · 11 hours ago
Machine Learning Engineer
United States
Full-time
Remote
Entry, Mid Level
$150K/yr - $185K/yr
2+ years exp
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Responsibilities
Design, implement, and manage scalable infrastructure for model training, testing, and deployment in a cloud-native environment.
Leverage infrastructure-as-code (e.g., Terraform, CloudFormation) to provision and maintain reproducible, version-controlled production environments.
Create robust, fully or partially automated CI/CD pipelines tailored for ML workflows, including data ingestion, feature engineering, model training, validation, and deployment.
Integrate model registries and feature stores to track model versions, lineage, and data provenance.
Ensure compliance with data governance, privacy, and security standards throughout the ML lifecycle.
Implement and enforce best practices for model governance, auditing, and documentation, ensuring reproducibility and trust in models.
Establish comprehensive observability frameworks for end-to-end monitoring of model performance, data quality, and system reliability.
Define and implement alerting and performance metrics to proactively identify and troubleshoot issues.
Conduct regular performance benchmarking and capacity planning to scale resources as models evolve.
Partner closely with data scientists, ML engineers, and DevOps engineers to streamline workflows, increasing team velocity and reducing friction from development to production.
Advocate for MLOps best practices and build self-service tooling that empowers teams to iterate quickly and safely on new model versions and features.
Qualification
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Required
Bachelor’s or Master’s degree in Computer Science or a related quantitative field.
2+ years of hands-on MLOps experience, including model deployment to production environments at scale.
Proven experience building and maintaining CI/CD pipelines specifically for ML, leveraging tools such as GitHub Actions, GitLab CI, Jenkins, etc.
Strong proficiency with AWS cloud services (e.g., Lambda, S3, API Gateway, ECR, SQS, SNS, Step Functions, CloudWatch, SageMaker) and containerization/orchestration platforms (Docker, Kubernetes, ECS/EKS).
Strong experience with Infrastructure-as-Code (IaC) tools, such as Terraform or CloudFormation, for provisioning, managing, and scaling cloud-native environments in a reproducible and efficient manner.
Familiarity with data versioning, experiment tracking (e.g., MLflow, Weights & Biases), and feature stores to streamline model development and iteration.
Experience deploying and optimizing deep learning models and LLMs in production, including performance tuning, distributed training, and GPU/accelerator integration.
Knowledge of security, compliance, and privacy best practices in ML, including role-based access controls, encryption strategies, and compliance frameworks (e.g., SOC 2, GDPR).
Understanding of advanced testing methodologies for ML systems (unit, integration, regression, A/B testing) and the ability to incorporate these into continuous integration workflows.
Strong problem-solving and analytical skills, capable of diagnosing complex issues in distributed, data-intensive environments.
Excellent communication and interpersonal skills, with the ability to effectively convey technical concepts to stakeholders at varying levels of technical expertise.
Proven ability to write, update, and maintain clear, comprehensive documentation for pipelines, processes, and infrastructure.
Track record of working effectively in cross-functional teams, adapting to shifting priorities, and delivering results in fast-paced, iterative development cycles.
Preferred
Familiarity with Agile methodologies (e.g., Scrum, Kanban) and experience contributing to sprints, backlogs, and retrospectives is a plus.
Benefits
Competitive salary and benefits package.
Company
CLARA Analytics
CLARA Analytics utilizes AI and data analytics to help insurance companies process and analyze large amounts of data related to claims.
51-200 employees
H1B Sponsorship
CLARA Analytics has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2023 (2)
2022 (3)
2021 (8)
2020 (6)
Funding
Current Stage
Growth StageTotal Funding
$60.5MKey Investors
Nationwide VenturesSpring Lake Equity PartnersAspen Capital Group
2024-02-21Series Unknown
2023-09-07Series C· $24M
2020-05-21Series B· $25M
Leadership Team
Eugene Wong
CFO
Greg Toll
VP, Self-Insured Sales
Recent News
Company data provided by crunchbase
