Overview
Full Time
Skills
FOCUS
Large Language Models (LLMs)
Predictive Analytics
IT Strategy
IT Management
Scalability
IaaS
Lifecycle Management
Training
Machine Learning (ML)
PyTorch
TensorFlow
scikit-learn
XGBoost
Machine Learning Operations (ML Ops)
Cloud Computing
Amazon Web Services
Google Cloud
Google Cloud Platform
Orchestration
Optimization
Python
SQL
Vector Databases
Leadership
Mentorship
Generative Artificial Intelligence (AI)
Big Data
Apache Hadoop
Apache Spark
Communication
Collaboration
LangChain
LlamaIndex
Microsoft Azure
Artificial Intelligence
Finance
Revenue Management
Management
Collections
Software Engineering
Continuous Integration
Continuous Delivery
Unit Testing
Job Details
Lead AI Engineer - Machine Learning & Generative AI
Position Overview
We are seeking a Lead AI Engineer to drive the design, development, and implementation of AI and machine learning solutions, with a strong focus on Generative AI, Large Language Models (LLMs), and predictive analytics. This role will lead technical strategy and execution, working closely with data scientists, software engineers, and product teams to deploy innovative AI-driven solutions at scale.
As a key technical leader, you will architect and optimize AI/ML pipelines, ensure best practices in MLOps, model deployment, and cloud-based AI solutions, and guide a team in solving complex business challenges. The ideal candidate will have a deep technical background, hands-on expertise in AI frameworks, and the ability to mentor and influence engineering teams.
Key Responsibilities
Required Qualifications & Experience
Preferred Skills & Industry Experience
Position Overview
We are seeking a Lead AI Engineer to drive the design, development, and implementation of AI and machine learning solutions, with a strong focus on Generative AI, Large Language Models (LLMs), and predictive analytics. This role will lead technical strategy and execution, working closely with data scientists, software engineers, and product teams to deploy innovative AI-driven solutions at scale.
As a key technical leader, you will architect and optimize AI/ML pipelines, ensure best practices in MLOps, model deployment, and cloud-based AI solutions, and guide a team in solving complex business challenges. The ideal candidate will have a deep technical background, hands-on expertise in AI frameworks, and the ability to mentor and influence engineering teams.
Key Responsibilities
- Lead the architecture, development, and deployment of advanced AI and ML models for real-world applications.
- Design and optimize retrieval-augmented generation (RAG) pipelines, multimodal AI systems, and model orchestration strategies.
- Provide technical leadership to AI/ML engineers and data scientists, ensuring best practices in scalability, performance, and security.
- Collaborate with cross-functional teams to translate business needs into high-impact AI solutions.
- Spearhead the adoption of MLOps best practices, including orchestration tools, cloud infrastructure, and monitoring frameworks for AI deployments.
- Automate and improve AI model lifecycle management, from data ingestion and preprocessing to training, validation, and deployment.
- Stay ahead of industry advancements in AI, ML, LLMs, and cloud computing, bringing in new methodologies and tools to enhance AI capabilities.
Required Qualifications & Experience
- 7+ years of hands-on experience in machine learning engineering, AI model deployment, and cloud-based AI solutions.
- Proficiency in leading ML frameworks such as PyTorch, TensorFlow, Scikit-learn, XGBoost, and MLOps tools.
- Deep expertise in cloud AI platforms (Azure, AWS, or Google Cloud Platform), including model deployment, orchestration, and compute optimization.
- Strong programming skills in Python, SQL, and experience working with data pipelines, vector databases, and large-scale AI systems.
- Proven ability to design and scale AI systems, ensuring efficient data handling, model performance, and operational stability.
- Leadership experience in mentoring, guiding technical teams, and setting AI strategy within an organization.
- Strong understanding of retrieval techniques, LLM-powered applications, and generative AI frameworks.
- Experience with Big Data technologies such as Hadoop or Spark is a plus.
- Excellent communication and collaboration skills, with the ability to present AI solutions to both technical and non-technical stakeholders.
Preferred Skills & Industry Experience
- Familiarity with LangChain, LlamaIndex, Haystack, Azure AI Studio, and retrieval-augmented generation (RAG) pipelines.
- Experience working in finance, revenue cycle management, or collections is a plus but not required.
- Knowledge of software engineering best practices, including CI/CD, unit testing, and code reviews.
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.