Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
Richmond, VA, United States
Posted
21 hours ago
DockerMicroservicesAWSMLOpsMLflowMachine LearningNLPNumPyScikit-learnAzureDeep LearningGenerative AIGoogle CloudKubernetesPandasPyTorchPythonRESTTensorFlow
Job Description
Job Title: Senior AI/ML Engineer
Location: Richmond, VA
Job Type: Contract
Experience: 12+ Years
Work Authorization: W2 Only — No C2C
Job Summary
We are seeking an experienced Senior AI/ML Engineer to design, develop, and deploy scalable Artificial Intelligence (AI) and Machine Learning (ML) solutions. The ideal candidate will have strong expertise in Python programming, machine learning algorithms, deep learning, model deployment, and cloud-based AI solutions.
Key Responsibilities
- Design, develop, and implement machine learning models to solve complex business problems.
- Build and optimize AI/ML pipelines for data processing, model training, evaluation, and deployment.
- Develop scalable AI/ML applications using Python and relevant frameworks.
- Work with structured and unstructured data to identify patterns and generate actionable insights.
- Implement deep learning, Natural Language Processing (NLP), and predictive analytics solutions.
- Deploy AI/ML models using AWS, Microsoft Azure, or Google Cloud Platform (Google Cloud Platform).
- Apply MLOps practices for model versioning, monitoring, automation, and continuous deployment.
- Collaborate with data engineers, software developers, architects, and business stakeholders.
- Monitor model performance, troubleshoot issues, and improve model accuracy and scalability.
- Follow best practices for data security, responsible AI, model governance, and documentation.
Required Skills
- 12+ years of overall IT experience with strong relevant AI/ML engineering experience.
- Strong programming skills in Python.
- Hands-on experience with machine learning algorithms and statistical modeling.
- Experience with TensorFlow, PyTorch, and scikit-learn.
- Knowledge of deep learning, NLP, and predictive modeling.
- Experience with Pandas, NumPy, and data processing techniques.
- Experience deploying and maintaining models in production environments.
- Knowledge of REST APIs, microservices, Docker, and Kubernetes.
- Experience with cloud-based AI/ML services on AWS, Azure, or Google Cloud Platform.
- Familiarity with CI/CD pipelines, model monitoring, and MLOps tools.
- Strong analytical, problem-solving, and communication skills.
Preferred Qualifications
- Experience with Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG).
- Familiarity with vector databases, embeddings, and prompt engineering.
- Experience with MLflow, Kubeflow, or similar MLOps platforms.
- Knowledge of data engineering, distributed computing, and big data technologies.
- Relevant cloud or AI/ML certifications are a plus.
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