AI/ML Technical Lead
Globenet Consulting Corp
Fort Belvoir, VA, United States
16 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Compensation
$130,000.0 - $155,000.0
Working hours
Regular working hours
Job source
Tech stack
Application Programming Interfaces (APIs)
Artificial Intelligence
Airflow
Amazon Web Services
Computer Vision
Microsoft Azure
Big Data
Cloud Database
Code Review
Continuous Integration
R (Programming Language)
Python (Programming Language)
+29 more
Machine Learning
Natural Language Processing
NumPy
Recommender Systems
Tensorflow
Software Deployment
Software Engineering
SQL Databases
Unstructured Data
Data Processing
Google Cloud
Feature Engineering
Pytorch
Large Language Models
Snowflake
Apache Spark
Deep Learning
Model Validation
Generative AI
Keras
Pandas
Scikit Learn
Kubernetes
Information Technology
HuggingFace
Xgboost
Machine Learning Operations
Docker
Databricks
Job description
We are seeking an AI/ML Technical Lead to design, build, and deploy scalable machine learning models and AI-powered solutions. This role will collaborate with engineering, product, data, and business teams to transform complex data into practical, measurable solutions. The ideal candidate has strong technical leadership, problem-solving skills, production AI/ML experience, and expertise in Large Language Models. Key Responsibilities
- Lead the design, development, training, testing, and deployment of AI and machine learning models.
- Build scalable ML pipelines for data processing, model training, validation, and production deployment.
- Work with structured and unstructured data, including text, images, documents, and large datasets.
- Collaborate with data engineers, software engineers, and product teams to integrate AI/ML capabilities into applications.
- Evaluate and improve model accuracy, efficiency, reliability, scalability, and performance.
- Develop predictive models, recommendation systems, NLP tools, automation workflows, and generative AI solutions.
- Research and apply modern AI/ML tools, techniques, architectures, and best practices.
- Monitor deployed models and address model drift, bias, data quality, and performance issues.
- Document model architecture, assumptions, limitations, metrics, and technical decisions.
- Promote responsible AI practices related to security, privacy, fairness, governance, and compliance.
- Provide technical direction, code reviews, mentoring, and implementation guidance to engineering teams.
Requirements
- Active Secret security clearance or higher.
- Bachelor’s degree in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, Engineering, or a related field.
- Three or more years of experience in AI, machine learning, data science, or software engineering.
- Strong Python programming skills.
- Experience with PyTorch, TensorFlow, Scikit-learn, Keras, XGBoost, or similar frameworks.
- Experience developing and deploying production machine learning models.
- Strong knowledge of algorithms, feature engineering, statistical analysis, and model evaluation.
- Experience processing large datasets using modern data tools.
- Familiarity with APIs, cloud platforms, and software development practices.
- Ability to communicate complex technical concepts to technical and non-technical stakeholders., * Master’s degree or PhD in a related field.
- Experience with Generative AI, LLMs, NLP, computer vision, or deep learning.
- Experience with Ask Sage, Hugging Face, LangChain, OpenAI APIs, Azure AI, AWS SageMaker, or Google Vertex AI.
- Experience with MLflow, Kubeflow, Airflow, Docker, Kubernetes, and CI/CD pipelines.
- Experience with SQL, Spark, Databricks, Snowflake, or cloud data warehouses.
- Knowledge of AI governance, ethics, bias testing, security, and data privacy standards.
- Experience deploying AI solutions in enterprise environments.
Technical Skills
- Languages: Python, SQL, and R
- ML Frameworks: PyTorch, TensorFlow, Scikit-learn, and XGBoost
- Cloud Platforms: AWS, Microsoft Azure, or Google Cloud
- MLOps: Docker, Kubernetes, MLflow, Airflow, and CI/CD
- Data Tools: Pandas, NumPy, Spark, Snowflake, and Databricks
- AI/LLM Tools: Ask Sage, Hugging Face, LangChain, OpenAI, and vector databases
Benefits & conditions
- Competitive salary
- Opportunity for advancement
- Training & development, In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role inclu…
- 3 days ago +
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