Bachelor's degree in a relevant technical field (Computer Science, Data Science, etc.)
Experience with Python and ML libraries (scikit-learn, pandas, NumPy)
Hands-on experience with Databricks for ML workflows
Familiarity with REST APIs and ML model deployment
Experience with Git and GitHub for version control
Strong analytical and problem-solving skills
Ability to collaborate in an Agile team environment
Responsibilities
Develop and optimize machine learning models for predictive analytics
Mentor junior developers and conduct peer code reviews
Design business logic and process models in a BPM-based system
Provide technical leadership to Agile teams
Integrate ML models with data pipelines and APIs
Monitor model performance and identify optimization opportunities
Document model architecture and technical decisions
Benefits
401(k)
Dental insurance
Health insurance
Paid time off
Vision insurance
Full Job Description
Benefits:
401(k)
Dental insurance
Health insurance
Paid time off
Vision insurance
The ML Engineer is responsible for developing, implementing, and optimizing machine learning models and data-driven solutions. Works closely with data engineers, developers, and stakeholders to prepare data, train and evaluate models, integrate ML capabilities, and support model deployment, monitoring, and continuous improvement.
We are seeking an ML Engineer for a contract position.
Position: ML Engineer
Position Type: Full-time-Remote
Role Specific Duties/ Role Responsibilities:
Solve highly complex technical problems using Appian and supporting platforms
Mentor junior developers and conduct peer code reviews
Design and develop business logic, process models/flows, and UI screens in a BPM-based system
Provide technical leadership to Agile development teams
Design architectural frameworks using industry-standard methodologies
Resolve systems integration issues and present technical material to senior client leadership
Machine Learning Development & Optimization:
Develop, train, test, and optimize machine learning models to support predictive analytics, classification, and data-driven decision-making.
Evaluate model performance, accuracy, and reliability to identify opportunities for improvement.
Support the development and enhancement of scalable, reusable ML capabilities.
Data Engineering & Feature Development
Support data ingestion, preprocessing, normalization, validation, and feature engineering across multiple data sources.
Develop data enrichment capabilities to improve model performance and analytical insights.
Assist in building reusable data pipelines and preparing datasets for model training, evaluation, and inference.
ML Integration & CI/CD Support
Integrate ML models with data pipelines, APIs, and application services to support operational use cases.
Support model packaging, version control, deployment automation, and CI/CD pipeline improvements.
Assist with deployment, troubleshooting, and production readiness activities across development, test, and production environments.
Testing, Validation & Performance Monitoring
Develop and execute model testing and validation procedures to assess accuracy, reliability, and performance.
Monitor model outputs and identify data quality issues, defects, and opportunities for optimization.
Support ongoing model evaluation, maintenance, and continuous improvement.
Agile Team Collaboration
Collaborate with data engineers, software developers, architects, and product stakeholders to align ML solutions with business and technical requirements.
Translate business needs into ML experiments, technical designs, and implementation tasks.
Contribute to technical planning, solution design, and delivery of new ML capabilities.
Documentation & Knowledge Management
Document model architecture, experiments, evaluation results, deployment procedures, and technical decisions.
Maintain technical documentation and implementation guidance to support knowledge transfer and maintainability.
Share findings, best practices, and lessons learned to improve team effectiveness and consistency.
Required Qualifications:
Bachelor's degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related technical field.
Equivalent combinations of relevant education, technical training, and professional experience may be considered.
Experience developing, training, evaluating, and optimizing machine learning models using Python and common ML libraries such as scikit-learn (sklearn), pandas, and NumPy.
Hands-on experience with Databricks for data processing, model development, experimentation, and ML workflows.
Experience with data preprocessing, feature engineering, data validation, and working with structured and semi-structured datasets.
Familiarity with ML model deployment, REST APIs, and integration with data pipelines or application services.
Experience with Git and GitHub for source control, collaboration, and code management.
Experience developing or maintaining CI/CD workflows using GitHub Actions, including automated testing, build processes, and deployment pipelines.
Understanding of ML model evaluation metrics, testing methodologies, and model performance monitoring.
Experience writing clean, maintainable, and well-documented Python code.
Strong analytical, problem-solving, troubleshooting, and communication skills.
Ability to collaborate effectively with cross-functional teams, including ML engineers, data engineers, software developers, and product stakeholders.
Ability to work collaboratively in an Agile team environment.
Preferred Qualifications
Relevant certifications or specialized training in machine learning, Databricks, cloud technologies, or MLOps.
Experience in government contracting, regulated industries, or large enterprises
Familiarity with identity, access management, data platforms, or enterprise SaaS ecosystems
Experience working with Jira and Confluence
Additional Requirements as per contract/client (Optional or Preferred):
Candidates must be a US Citizen or a Legal Permanent Resident (Green Card status) for 3 years and be Federal Tax compliant.
This is a remote position.
Compensation: $120,000.00 - $150,000.00 per year
About NeboWeb Internet Marketing
NeboWeb is a full-service digital marketing agency that specializes in SEO, PPC, social media, and web design. The company was founded in 2004 and is headquartered in Atlanta, Georgia. NeboWeb has worked with clients such as the American Cancer Society, Chick-fil-A, and the University of Georgia. The company has won numerous awards for its work, including a Webby Award and a W3 Award.
