Sr. Machine Learning (ML) Engineer

Synergy Business Innovation & Solutions is a premier implementer of cutting-edge software solutions. Synergy brings the experience and expertise necessary to deliver capability that provides tangible ROI to our customers. Synergy’s core areas of expertise are in the fields of Digital Transformation, Cloud Solutions, SaaS and Low-Code/No-Code solutions, Emerging Technologies, Data analytics and Visualization, Information Assurance, and Business Process Re-Engineering.

Synergy offers its employees a generous portfolio of core and voluntary benefits including group medical, dental, and vision insurance, HSA, FSA, 401(k) with immediately vested company match, PTO/Sick Leave, 11 paid federal holidays, company paid life, short-term and long-term disability insurance, tuition and training reimbursement, fitness/wellness reimbursement, a referral bonus program, and life management programs.

At Synergy, you’ll be challenged and given the opportunity to grow in your career path. In fact, growth is such a big deal to us that you will have dedicated career coaches available for every employee, company-funded certification opportunities, education reimbursement, and a general open-door policy so that you have support when you need it. Our team is eager to learn, fast-paced, and quality-driven—if that sounds like you, Synergy has a position for you!

This position is designated as work-from-home.DescriptionAs a Senior Machine Learning (ML) Engineer with Synergy, you will join the team supporting the mission of the Officer of the Chief Information Officer for a Federal government agency. In collaboration with the Synergy Program Technical Lead and Artificial Intelligence (AI) team, the candidate will execute projects under the direction of the customer’s AI division leadership. The candidate will provide expertise to perform end-to-end development plus explore innovative applications and techniques in natural language processing, applied ML, and explainable plus privacy-aware Responsible AI/MLEssential Functions & Duties

• Develop, train, test, and deploy ML models to production with robust monitoring and logging
• Study and transform data science prototypes, select suitable data sets, and conduct data collection and modeling
• Perform statistical analysis and tune hyper-parameters to enhance model performance
• Automate workflows for data collection, model training, and deployment
• Implement continuous integration/continuous deployment (CI/CD) pipelines for ML projects
• Monitor models in production and optimize performance over time
• Work with data scientists to transition models from development to production
• Document processes and provide knowledge transfer to other team members or teams
• Evaluate and apply new tools and technologies to enhance ML operations (MLOps) practices
• Lead customer communications and project presentations related to ML development
• Coordinate with a peer ML Engineer on tasks and provide subject matter expertise to subordinate ML Engineers
• Collaborate with cross-functional engineering and operations teams to deliver solutions

Skills, Qualifications and Certifications of Best Candidates

• Experience in developing and deploying ML models at scale
• Proficiency with ML frameworks such as TensorFlow, PyTorch, or similar
• Experience implementing MLOps principles, including version control and CI/CD
• Familiarity with infrastructure automation tools (e.g., Docker, Kubernetes)
• Experience with cloud services implementing APIs for model deployment (e.g., AWS SageMaker, Azure ML)
• Strong programming skills in Python, R, Bash, and/or other related languages for automation
• Ability to clearly communicate/present technical issues and status to customers
• Ability to create project documentation (e.g., SOP) and user guidance
• Proficient with Microsoft Office 365 applications, specifically Word, Excel, PowerPoint, Outlook, OneDrive, Teams, and SharePoint
• Experience working in an agile environment, coordinating across multiple teams
• Ability to execute in a remote work environment
• Experience with Federal government customers preferred

 Preferred Certifications (Desired but not Required)

• AWS Certified Solutions Architect (Highly Desired)
• Microsoft Certified Azure Solutions Architect Expert (Highly Desired)
• Google Cloud Professional Cloud Architect

 Citizenship or Work Authorization RequiredUS Citizen or US Work Authorization

Preferred Education & Experience: 6 years of experience and a Bachelor’s Degree in Computer Scienc