Overview
Remote
Depends on Experience
Contract - W2
Contract - Independent
Skills
Agile Management
Accessibility
Amazon Web Services
Artificial Intelligence
Bash
Cascading Style Sheets
Cloud Computing
Clustering
Collaboration
Computer Networking
Data Cleansing
Data Processing
Data Quality
Databricks
Docker
Forecasting
Generative Artificial Intelligence (AI)
HTML
JavaScript
Kubernetes
Linux
Machine Learning (ML)
Machine Learning Operations (ML Ops)
Management
Mentorship
Microsoft Azure
Microsoft Windows
NumPy
OS X
Open Source
Operating Systems
Software Engineering
Time Series
Use Cases
User Experience
Version Control
Pandas
Prompt Engineering
PyTorch
Python
Regression Analysis
Testing
Visualization
Windows PowerShell
scikit-learn
Git
Job Details
Title: Senior AI/ML Engineer
Remote
- 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
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.