AI/ML Technical Lead

Globenet Consulting Corp

  • Bellevue, Washington
  • 23 days ago

    Highlights

    In the last 20 years, we have developed innovative best-in-class technology solutions to the world’s forward-thinking companies on four key service areas: - Customer Experience: engaging customers with differentiating digital experiences to sustain. The ideal candidate has strong technical leadership, problem-solving skills, production AI/ML experience, and expertise in Large Language Models.

    Numbers & Facts

    LocationBellevue, Washington
    Websitewww.theaesgroup.com

    Description

    Benefits:
    • Competitive salary
    • Opportunity for advancement
    • Training & development
    Role: AI/ML Technical Lead
    Location: Fort Belvoir, VA 22060

    Let’s Create Our Future Together at The AES Group!

    Position Overview
    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.
    Required Qualifications
    • 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.
    Preferred Qualifications
    • 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
    Compensation: $130,000.00 - $155,000.00 per year




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