Senior Machine Learning Engineer

CLARA Analytics

full-time

Posted on: 9/20/2025

Origin: • 🇺🇸 United States

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💰 $165,000 - $200,000 per year

Senior

AWSCloudDistributed SystemsDockerElasticSearchKubernetesPythonScikit-LearnSparkTerraform

About the role

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
Report directly to the VP of Data Science and collaborate with data scientists, MLOps engineers, data engineers, and product stakeholders

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
Legally authorized to work in the United States without sponsorship (NOTE: we are unable to sponsor)
Preferred: Familiarity with large-scale data processing, vector databases, or knowledge graph technologies
Preferred: Knowledge of bias detection, fairness metrics, and responsible AI practices
Preferred: Background in software engineering best practices (design patterns, code quality, testing frameworks)
Preferred: Domain expertise in industries such as insurance, healthcare, or finance
Preferred: Hands-on work with LLMs, transformers, or other foundation models (fine-tuning, RAG pipelines, serving at scale)
Preferred familiarity with Spark, Docker, Kubernetes, AWS SageMaker, MLFlow, EKS, Athena, S3, EMR, ElasticSearch, OpenAI, LangChain, Scikit-learn, OpenTelemetry, Terraform or other IaC technology