Sr. FullStack AI/ML Solution Architect - Remote - Need 12+ years
Posted 2 days ago by 1764165481
Negotiable
Outside
Hybrid
USA
Summary: The role of IT Application Solutions Architect Senior AI/ML Engineer involves designing and implementing advanced AI/ML models, developing generative AI solutions, and managing the full model lifecycle. The position requires expertise in modern code development, MLOps, and collaboration with cross-functional teams to enhance AI/ML practices. The role is primarily remote with occasional office visits in Washington DC. Candidates should have a strong background in Python and various AI/ML libraries, along with experience in Agile methodologies.
Key Responsibilities:
- Design and implement supervised and unsupervised AI/ML models.
- Develop and integrate generative AI solutions powered by LLMs.
- Write efficient, maintainable Python code and deploy solutions using Docker and Kubernetes.
- Manage MLOps and the full model lifecycle, deploying models using FastAPI.
- Drive platform adoption using Databricks and support model automation.
- Perform advanced data processing, visualization, and storytelling.
- Approach problems with a systems thinking mindset, translating business goals into technical solutions.
- Collaborate with teams and mentor junior engineers and data scientists.
Key Skills:
- Experience with Agile project management methodologies.
- Expertise in Python, PowerShell, Bash, or JavaScript.
- Working knowledge of Linux, MacOS, Windows, and mobile operating systems.
- Understanding of modern computer networking technologies.
Salary (Rate): undetermined
City: Washington DC
Country: USA
Working Arrangements: hybrid
IR35 Status: outside IR35
Seniority Level: undetermined
Industry: IT
Role: IT Application Solutions Architect Senior AI/ML Engineer
Location: Remote (Quarterly once need to go office) Washington DC
- AI/ML Development: Design and implement supervised and unsupervised models including regression, classification, clustering, time-series forecasting, and boosting methods. Build and fine-tune neural networks including CNNs, RNNs, and LSTMs.
- Generative AI: Develop and integrate solutions powered by LLMs and open-source foundation models. Evaluate and optimize model performance, latency, and cost. Stay current with advances in foundation models, prompt engineering, fine-tuning techniques (LoRA, PEFT), and model safety practices.
- Modern Code Development: Write efficient, maintainable Python code (advanced Python required), using tools like JupyterLab and VSCode for development and testing. Package and deploy solutions using Docker and Kubernetes on cloud platforms like AWS and Azure. Use Git for version control and champion SWE best practices.
- Model Management and Deployment: Manage MLOps and full model lifecycle. Serialize and manage models using Pickle, Joblib, and/or ONNX. Deploy models using FastAPI and serverless functions, building secure and scalable endpoints. Create user-facing AI tools using Streamlit and front-end technologies (HTML/CSS/JavaScript).
- Platform Enablement: Databricks expertise to drive platform adoption and accelerate the development of new use cases, supporting model automation, AutoML, and template-based development.
- Hands-on:Advanced data processing, visualization, and storytelling. Solid background in popular AI/ML open-source libraries including scikit-learn, PyTorch, pandas, polars, NumPy, seaborn, and other libraries for data cleaning, feature engineering, and visualization.
- Systems Thinking:Approach problems with an end-to-end mindset, considering model performance, data quality, infrastructure, user experience, and downstream applications. Translate business goals into viable, scalable technical solutions.
- Collaboration & Mentorship: Work closely with cross-functional teams and mentor junior engineers and data scientists for the overall improvement of data quality metrics, solution accessibility, self-service capabilities, governance, and business adoption of AI/ML best practices.
Minimum Skillset Requirements:
- Experience with Agile project management methodologies
- Expertise in one or more of: Python, PowerShell, Bash or JavaScript.
- Working knowledge of Linux, MacOS, Windows, and mobile operating systems, platforms and internals
- Working knowledge of modern computer networking technologies