AI/ML Developer

Amivero•Dallas, TX

About The Position

Amivero’s team of IT professionals delivers digital services that elevate the federal government, whether national security or improved government services. Our human-centered, data-driven approach is focused on truly understanding the environment and the challenge, and reimagining with our customer how outcomes can be achieved. Our team of technologists leverage modern, agile methods to design and develop equitable, accessible, and innovative data and software services that impact hundreds of millions of people. As a member of the Amivero team you will use your empathy for a customer’s situation, your passion for service, your energy for solutioning, and your bias towards action to bring modernization to very important, mission-critical, and public service government IT systems. The AI/ML Engineer designs, develops, trains, and deploys machine learning models to support predictive analytics, anomaly detection, and decision-support capabilities. This role integrates AI/ML solutions into operational workflows, collaborating with data, product, and engineering teams to ensure models are effective, scalable, and aligned with organizational objectives .

Requirements

US Citizenship Required to obtain Public Trust
Active DHS Clearance (preferred)
Bachelor Degree + 10 years of experience
3+ years of experience developing and optimizing solutions using Python or similar, with a strong focus on performance, scalability, and efficiency
Extensive experience working with vector technology databases, designing and implementing solutions to efficiently store, search, and analyze high-dimensional data for real-time and large-scale applications
Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field; a master’s degree preferred. A bachelor’s degree with an additional three (3) or more years of relevant experience may substitute for a master’s degree.
Minimum of five (5) years of directly related experience in AI/ML development, data science, or applied analytics.
Hands-on experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
Strong programming skills in Python, Java, or R; experience with APIs and integration into production systems.
Knowledge of data preprocessing, feature engineering, model evaluation, and deployment pipelines.
Familiarity with cloud platforms (AWS, Azure, GCP) for AI/ML workloads.
Excellent analytical, problem-solving, and critical-thinking skills.
Strong communication and collaboration skills, with the ability to work with cross-functional teams.

Nice To Haves

Experience mentoring or guiding less experienced AI/ML engineers is a plus.

Responsibilities

Design, develop, and deploy machine learning models to support predictive analytics, anomaly detection, and decision-support tools.
Integrate AI/ML solutions into operational systems and workflows to enhance automation and efficiency.
Create and fine-tune algorithms for various tasks such as classification, regression, clustering, and recommendation systems.
Preprocess, clean, and transform data to ensure high-quality inputs for model training.
Develop models leveraging advanced machine learning techniques, including deep learning, reinforcement learning, and natural language processing.
Build and maintain scalable and efficient data pipelines using Databricks and Hadoop/Cloudera.
Implement ETL processes to clean, prepare, and transform large datasets for analysis and modeling.
Ensure data integrity and quality throughout the data lifecycle.
Evaluate model performance using appropriate metrics and implement improvements as needed.
Collaborate with data engineers, product managers, and developers to align AI/ML solutions with program goals.
Implement best practices for model versioning, deployment, monitoring, and retraining.
Ensure compliance with data privacy, security, and regulatory standards in AI/ML workflows.
Document model design, assumptions, data sources, and performance results.
Stay current with emerging AI/ML technologies, frameworks, and research to enhance solutions.
Mentor junior team members and contribute to knowledge sharing in AI/ML development practices.