Senior Machine Learning Engineer (MLE)

About CLARA

CLARA Analytics is the leading AI as a service (AIaaS) provider that improves casualty claims outcomes for commercial insurance carriers and self-insured organizations. The company’s product suite for workers comp, commercial auto and general liability insurance claims applies image recognition, natural language processing, and other AI-based techniques to unlock insights from medical notes, bills and other documents surrounding a claim. CLARA’s customers include companies from the top 25 global insurance carriers to large third-party administrators and self-insured organizations. Founded in 2017, CLARA Analytics is headquartered in California’s Silicon Valley. For more information, visit www.claraanalytics.com.

About the Role

We are seeking a Senior Machine Learning Engineer (MLE) to design, build, and scale advanced machine learning systems that power critical business outcomes. This role, which reports directly into the VP of Data Science, will involve collaborating with data scientists, machine learning operations engineers, data engineers, and product stakeholders to transform complex problems into production-ready solutions. The ideal candidate combines deep technical expertise in ML with strong software engineering skills, enabling reliable, interpretable, and scalable deployments.

What You’ll Do...

• Design, train, and optimize machine learning model architectures for production use cases
• Build and maintain robust ML pipelines for data ingestion, feature engineering, training, and deployment
• Collaborate with data scientists to move research prototypes into production environments
• Implement model monitoring, retraining strategies, and performance diagnostics to ensure reliability
• Develop scalable APIs and services that expose ML capabilities to downstream systems
• Apply best practices in MLOps, CI/CD, and AWS-native deployments
• Ensure explainability, fairness, and compliance in ML solutions
• Conduct code and model reviews of your peers, providing actionable feedback to ensure a high standard of quality
• Contribute to technical standards across the ML team

What We’re Looking For...

Required

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Statistics, or related field
• 5+ years of experience in machine learning and software engineering roles
• Strong proficiency in Python and ML libraries
• Experience with data engineering tools and distributed systems
• Solid understanding of algorithms, model evaluation, and statistical methods
• Hands-on experience with containerization, orchestration, and cloud ML services
• Track record of deploying and maintaining ML models in production at scale
• Strong communication skills and ability to work cross-functionally

Preferred

• Familiarity with large-scale data processing, vector databases, or knowledge graph technologies
• Knowledge of bias detection, fairness metrics, and responsible AI practices
• Strong background in software engineering best practices (design patterns, code quality, testing frameworks)
• Domain expertise in industries such as insurance, healthcare, or finance where compliance and explainability are critical
• Hands-on work with LLMs, transformers, or other foundation models (fine-tuning, RAG pipelines, serving at scale)
• Familiarity with systems current MLEs and adjacent teams regularly work with (Spark, Docker, Kubernetes, AWS SageMaker, MLFlow, EKS, Athena, S3, EMR, ElasticSearch, OpenAI, LangChain, Scikit-learn, OpenTelemetry, Terraform or other IaC technology)

What We Offer...

• The opportunity to make a real impact on a growing company.
• Collaborative and supportive work environment.
• Competitive compensation package.
  • Salary + Bonus
  • Benefits: employer-provided health insurance and ancillary benefits (life, disability, etc.), flexible PTO, fully remote, 401k with match
• Be a part of a team that is passionate about what we do!