Machine Learning (ML) Engineer
United States
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 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
- Collaborate with cross-functional engineering and operations teams to deliver solutions
- 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
- AWS Certified Solutions Architect (Highly Desired)
- Microsoft Certified Azure Solutions Architect Expert (Highly Desired)
- Google Cloud Professional Cloud Architect
Preferred Education & Experience: 7 years of technical experience and a Bachelor’s Degree in Computer Science, Information Management (IM), Information Technology, Engineering, or equivalent; IT Solutions management experience preferred.
Compensation for roles at Synergy varies depending on a wide variety of factors including but not limited to the requirements of the role; education and certifications; knowledge, training, skills and abilities; level of experience; geographic location; and alignment with market data, law, and other business and organizational needs. As required by local law, the posted pay range represents the lowest to the highest pay that Synergy believes in good faith it might pay for this particular job, depending on the circumstances. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. It is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case.
A reasonable estimate of the current pay range is: $95,000 – $125,000.
Synergy will accept applications for this role until December 27, 2024
Essential Job Function Physical Requirements: The physical requirements of this position are critical in evaluating the qualifications and abilities of an applicant or employee. The physical efforts needed to perform the essential duties of this job 90% of the time are repetitive motions, grasping, holding, and finger dexterity of the hands, reading, writing, eye-hand coordination, color distinction, and full visual abilities, hearing, talking, sitting, and use of IT equipment, phones, and office machines.
To a reduced degree, <30% of the time, candidates may have to stand, walk, lift 0-30 pounds, push or pull objects, climb stairs, bend, squat, reach, drive a car, or work overtime.
Synergy is an equal opportunity employer, and does not discriminate against applicants for employment or its employees on the basis of age, race (including hair texture/style), creed, color, religion, religious creed, ancestry, national origin, ethnic origin, sexual orientation, gender identity or expression, military or veteran status, sex, medical condition, pregnancy (childbirth, breastfeeding, and related medical conditions), physical or mental disability, personal appearance, organ donation and hair length associated with race, genetic information or characteristics, family responsibilities, familial status, marital status, citizenship or immigration status, status as a victim of domestic violence, a sexual offense, or stalking, political affiliation, arrest records and criminal convictions, credit information, matriculation, homeless status, or any other characteristic protected by federal, state and local law. Discrimination or harassment based upon these protected categories is expressly prohibited. This policy applies to all aspects of employment, including job selection, assignment, promotion, compensation, benefits, training, discipline and termination.
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Work-from-home only
Benefits/Perks401(k) match Career coaching Certification opportunities Dental Disability Insurance Fitness Reimbursement Life Insurance Life management programs Medical Paid holidays PTO Referral Bonus Tuition reimbursement Vision Vision Insurance Wellness reimbursement
Tasks- Automate workflows
- Collaborate with cross functional teams
- Develop and deploy ML models
- Monitor and optimize model performance
Agile APIs Applied ML Automation AWS AWS SageMaker Azure Azure ML Bash Business Process Re-engineering CI/CD Cloud solutions Digital Transformation Docker Documentation Emerging Technologies Explainable AI Information Assurance Kubernetes Low-code/No-code Low-code/no-code solutions Machine Learning Microsoft Office 365 MLOps Natural Language Processing No-code solutions Organizational Privacy-Aware AI Python PyTorch R SaaS TensorFlow Training Visualization
EducationComputer Science Engineering Information Technology
TimezonesAmerica/Anchorage America/Chicago America/Denver America/Los_Angeles America/New_York Pacific/Honolulu UTC-10 UTC-5 UTC-6 UTC-7 UTC-8 UTC-9