Senior AI​/ML MLOps Engineer

Salary: $114, per year

• Strong grounding in data science, machine learning, statistics, and predictive modeling, including practical knowledge of supervised and unsupervised techniques.
• Experience with feature engineering, model selection, hyperparameter tuning, validation, and performance assessment.
• Proficiency in Python and familiarity with SQL; experience using frameworks such as Scikit-learn, Tensor Flow, PyTorch, or XGBoost.
• Demonstrated ability to manage machine learning solutions from experimentation through production, including experiment tracking, model registries and versioning, dataset and model lineage, reproducibility, deployment, monitoring, drift detection, and automated retraining.
• Hands-on knowledge of MLOps methods and tools, such as MLflow, Kubeflow, Azure Machine Learning, AWS Sage Maker, Google Vertex AI, or Databricks.
• Experience developing automated ML pipelines and connecting them to CI/CD workflows; familiarity with Docker, Kubernetes, Git, and platforms such as Azure Dev Ops, Git Hub Actions, or Jenkins.
• Experience automating end-to-end ML life cycles with Kubeflow and Vertex AI, tracking and registering experiments and models with MLflow, and detecting data or model drift with Evidently.
• Experience with at least one of Azure, AWS, or GCP, plus knowledge of data engineering, ETL/ELT pipelines, data quality, SQL or No
  
  SQL databases, large datasets, scalable data processing, and cloud storage.
• Preferred: experience with generative AI, LLMs, RAG, NLP, conversational AI, or LLMOps and GenAI lifecycle management.
• Preferred: experience with Databricks or Spark, feature stores, and data or model versioning tools.
• Preferred: knowledge of model governance, explainability, responsible AI, or AI security; healthcare AI/ML experience; and familiarity with Agile/Scrum delivery.
• Preferred: experience spanning model development and fine-tuning, evaluation, data pipelines, feature engineering, and end-to-end AI solution development.

• Design, develop, deploy, and manage machine learning solutions throughout the ML lifecycle.
• Operationalize models at scale by building and maintaining automated training and deployment pipelines, model versioning and experiment tracking, monitoring and drift detection, and CI/CD processes.
• Collaborate with Data Scientists, Data Engineers, Cloud/Dev Ops teams, architects, and product stakeholders to deliver scalable, reliable AI/ML solutions.

• AI
• AWS
• Azure
• CI/CD
• Cloud
• Databricks
• Dev Ops
• Docker
• ETL
• Fine-tuning
• GCP
• Git
• Git Hub
• Jenkins
• Kubeflow
• Kubernetes
• Machine Learning
• MLflow
• MLOps
• No
  
  SQL
• Py Torch
• Python
• RAG
• SQL
• Security
• Spark
• Tensor Flow

We are seeking an experienced AI/ML Engineer with a strong data science background. The pay range is $55–$60 per hour. Paid sick leave is provided where required by law; benefit eligibility and terms vary by employment status, service length, and work location, and plans may be changed in accordance with applicable laws. We are Cynet Systems Inc., founded in 2010 and headquartered in the Washington, DC metro area.

We provide technology staffing and workforce solutions to Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada, supporting IT, engineering, life sciences, clinical, and professional staffing. We are a certified Minority Business Enterprise and hold ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II certifications.

• medical insurance
• dental insurance
• vision insurance
• 401(k)
• health savings account
• disability and life insurance
• supplemental coverage
• identity theft protection
• pet insurance
• wellness programs
• employee assistance program
• career development opportunities
• Paid sick leave is provided where required by law