Machine Learning Engineer Jobs

About The Position

Requirements

• Ability to hold a position of public trust with the U.S. government.
• Bachelor’s degree in computer science, data science, statistics, information systems, engineering, business, or a related scientific or technical discipline.
• 5–7 years of industry experience developing ML/AI solutions and solving complex problems.
• 5–7 years of experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn.
• Strong programming skills in languages such as Python, R, or Java.
• Solid understanding of statistical methods, data structures, and algorithms.
• Experience with data preprocessing, feature engineering, and model evaluation techniques.
• Experience working with distributed data processing frameworks such as Apache Spark.
• Hands-on experience developing and deploying machine learning solutions within Databricks (DBX) environments.
• Experience developing and deploying machine learning workflows within Databricks, including use of MLflow or similar model lifecycle tools.
• Knowledge of cloud platforms such as AWS, Google Cloud, or Azure.
• Experience with version control systems (e.g., Git) and CI/CD practices.
• Excellent problem-solving skills and attention to detail.
• Strong communication skills and ability to work collaboratively in a team environment.
• Ability to manage multiple tasks and projects simultaneously while meeting deadlines.

Responsibilities

• Collaborate with cross-functional teams to design and develop machine learning models and algorithms to address business needs.
• Analyze and process large-scale datasets using distributed data processing frameworks (e.g., Spark) to extract meaningful insights and patterns.
• Collaborate with cross-functional teams to integrate machine learning solutions into existing systems and workflows.
• Optimize and fine-tune machine learning models for performance, scalability, and accuracy.
• Implement and maintain data pipelines to support machine learning workflows within Databricks environments.
• Utilize Databricks capabilities (e.g., notebooks, jobs, workflows, MLflow) to develop, track, and manage machine learning experiments and model lifecycle.
• Evaluate the effectiveness of machine learning models using appropriate metrics and validation techniques.
• Document processes, experiments, and results to ensure reproducibility and knowledge sharing.
• Deploy machine learning models to production environments and monitor their performance.
• Contribute to the growth of our AI & Data Exploitation Practice.

Benefits

• The projected compensation range for this position is $140,000 to $190,000.
• Annual salary is just one aspect of Steampunk’s total compensation package for employees.
• Learn more about additional Steampunk benefits here.