Overview
$DOE
Accepts corp to corp applications
Contract - Long Term
Skills
Python
API
Deployment
Machine Learning
Data Pipelines
Metrics
Workflow
Application Development
Problem-Solving
Data Analysis
Data Structures
Apache
Data Visualization
Datasets
Data Science
Production Environment
Data Management
Artificial Intelligence
PyTorch
Statistics
Cortex
Job Details
JobTitle: AI/ML Engineer
Location: Boston, MA / Tampa, FL / Jersey City, NJ (3 days/week onsite)- locals only
Exp level : 14+ years
No relocation candidates F2F will be required
Summary:
We're seeking a passionate, hands-on AI/ML Engineer to join our dynamic Technology Research and Innovation team, where you'll play a pivotal role in spearheading AI initiatives and innovation. As an AI/ML Engineer, you will play a pivotal role in designing, developing, and deploying Artificial Intelligence systems that solve complex problems and drive our technological advancement.
Qualifications:
- Bachelor's or Master's degree in computer science, Statistics, Data Science, or a related field.
- 6+ years of experience in Machine Learning and Data Science.
- Strong programming skills in Python
- Experience working with large datasets and performing data analysis.
- Experience with Machine Learning, Data Visualization, and Generative AI libraries and frameworks (e.g., Pandas, NumPy, Matplotlib, Seaborn, TensorFlow, PyTorch, scikit-learn, LangChain, LangGraph).
- Experience in Prompt Engineering, LLMOps, LLM Fine Tuning, and evaluation techniques
- Proven experience in developing and deploying machine learning models in a production environment.
- Strong understanding of Generative AI, Retrieval Augmented Generation, Agentic AI Workflow, Statistical methods, data structures, and algorithms.
- Experience with Snowflake Data Pipelines (stream, task, UDF) and Cortex features is a plus
- Experience with AWS Sage Maker, Bedrock, and AWS cloud platform for deploying AI solutions.
- Experience in building Asynchronous Python APIs for model inferencing.
- Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau.
- Previous experience in a similar role or industry is preferred.
- Excellent communication and collaboration skills.
- Strong problem-solving skills and analytical thinking
- Passion for learning and staying up-to-date with the latest advancements in AI field
Responsibilities:
Generative AI Application Development- Develop and implement AI solutions such as Retrieval-Augmented Generation (RAG) and Agentic AI Workflows using advanced techniques in prompt engineering and fine-tuning of Large Language Models (LLMs).
- Conduct thorough evaluations of LLMs to ensure the models meet the desired performance criteria and are aligned with business goals.
- Collaborate with cross-functional teams to integrate AI solutions into existing systems and workflows, enhancing overall efficiency and capabilities.
- Design and develop machine learning models and algorithms to address business challenges and improve product features.
- Deploy machine learning models in production environments to ensure scalability and efficiency.
- Optimize and refine models based on performance metrics and feedback.
Data Management
- Collect, clean, and preprocess data from various sources to create robust datasets for training and evaluation.
- Implement data augmentation and feature engineering techniques to enhance model performance.
- Maintain and manage data pipelines to ensure seamless data flow and integration.
Python API Development
- Develop scalable APIs in python (fastApi, Apache, Gunicorn, uvicorn) for model inferencing
- Stay updated with the latest trends and advancements in AI and machine learning technologies.
- Conduct research to explore new methodologies and techniques that can be applied to current and future projects.
- Collaborate with cross-functional teams to drive innovation and implement cutting-edge solutions.
- Work closely with software engineers, data scientists, and product managers to align AI/ML initiatives with business goals.
- Communicate complex technical concepts and results to non-technical stakeholders in a clear and concise manner.
- Provide mentorship and guidance to junior team members and contribute to the upskilling of the team.
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