Machine Learning Engineer
Data Science & AI Innovation
Machine Learning Engineer
Richmond, VAFull Time
Role Details for Machine Learning Engineer
About The Machine Learning Engineer Role
Key Responsibilities Design and implement scalable machine learning models and pipelines Work with large-scale datasets to develop classification, regression, NLP, and time series forecasting solutions Collaborate with data engineers to ensure proper data collection, transformation, and feature engineering Deploy models to production using MLOps practices (Docker, CI/CD, model versioning) Conduct model performance evaluation, tuning, and retraining cycles Research and apply state-of-the-art techniques and open-source frameworks Communicate findings to stakeholders with clear visualizations and reports Support proposal development and client engagements involving AI/ML scopes
Key Responsibilities for Machine Learning Engineer
Required Qualifications For Machine Learning Engineer
Precise Analytics is a data engineering and AI firm headquartered in Richmond, VA. We deliver data engineering, business intelligence, and machine learning solutions to government and commercial clients — and we operate a specialized AI Workforce Solutions division that supplies skilled human contributors to leading AI training platforms. We are committed to building a technically excellent team.
Precise Analytics is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, veteran status, or any other characteristic protected by law.
Machine Learning Engineer
Richmond, VAFull Time
Role Details for Machine Learning Engineer
About The Machine Learning Engineer Role
Key Responsibilities Design and implement scalable machine learning models and pipelines Work with large-scale datasets to develop classification, regression, NLP, and time series forecasting solutions Collaborate with data engineers to ensure proper data collection, transformation, and feature engineering Deploy models to production using MLOps practices (Docker, CI/CD, model versioning) Conduct model performance evaluation, tuning, and retraining cycles Research and apply state-of-the-art techniques and open-source frameworks Communicate findings to stakeholders with clear visualizations and reports Support proposal development and client engagements involving AI/ML scopes
Key Responsibilities for Machine Learning Engineer
Required Qualifications For Machine Learning Engineer
- Must-Have Qualifications
- Bachelor’s or Master’s in Computer Science, Data Science, Machine Learning, or a related field
- 3+ years of experience building and deploying ML models in production
- Proficiency in Python and ML libraries (scikit-learn, TensorFlow, PyTorch, XGBoost)
- Strong understanding of data structures, algorithms, and statistics
- Experience with cloud platforms (AWS, Azure, or GCP) and containerization tools (Docker, Kubernetes)
- Familiarity with MLOps tools (MLflow, SageMaker, Vertex AI, etc.)
- Excellent problem-solving, communication, and documentation skills
- Nice to Have
- Experience with NLP frameworks (spaCy, Hugging Face Transformers)
- Familiarity with Spark or distributed ML frameworks
- Prior experience working on federal data science or analytics contracts
- Knowledge of data privacy and compliance (GDPR, HIPAA, FedRAMP)
Precise Analytics is a data engineering and AI firm headquartered in Richmond, VA. We deliver data engineering, business intelligence, and machine learning solutions to government and commercial clients — and we operate a specialized AI Workforce Solutions division that supplies skilled human contributors to leading AI training platforms. We are committed to building a technically excellent team.
Precise Analytics is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, veteran status, or any other characteristic protected by law.
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