About Moser

For more than 25 years we have formed partnerships and grown through open and honest collaboration with our clients, partners, and employees. We are best known for taking great care of our clients, our dedication to creating a work environment where employees do their best work, and our deep commitment to continuous improvement. Our consultants work in a collaborative and fast-paced environment, are self-motivated, and are passionate about evolving technology. It is no accident that we are recognized as one of the Best Places to Work in Indiana for 10 consecutive years.

Internally, we believe in building strong teams from the top down with a focus on values in our Model-Coach-Care philosophy. Our leadership are encouraged and trained to model good practices, mentor other employees and each other, and show empathy and caring in all interactions. This is the base of our core values: Accountability, Balance, Collaboration, Focus, Integrity, Social Responsibility, Support and Transparency.

Moser Consulting believes in equal opportunity for all people and is committed to enabling a diverse, equitable, and inclusive culture. We foster a spirit of unity that respects the remarkable individuality of everyone's culture, history, and service.

Description

We are seeking a highly skilled and motivated Machine Learning Engineer/AI Developer with 3+ years of hands-on experience to join our dynamic team. The ideal candidate will have deep expertise in designing, developing, and deploying ML models and AI systems using Python, with strong proficiency in modern frameworks such as PyTorch, TensorFlow. Experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and foundation model fine-tuning is essential. This role will also encompass 50% Data Engineering work such as pipeline development and python heavy ELT and thus cloud engineering experience is critical.

This role is ideal for someone who enjoys working on different types of projects - from data ingestion and transformation to model development, deployment, and monitoring. We are looking for someone who thrives in a fast-paced, collaborative environment and is passionate about pushing the boundaries of AI technology to solve complex problems.

Role Responsibilities

Data Engineering:

• Design, Develop, Deploy, and Monitor complex ETL/ELT data pipelines which may contain various required transformations of data using various languages and techniques.
• Apply and promote best practices for data engineering including governance, scalability, and deployment standards.
• Ensure data quality and integrity by implementing data validation, cleansing, and transformation processes.
• Create and maintain technical documentation, operational documentation, data flow diagrams, and data mapping documents.
• Provides technical leadership and mentorship to team members.

AI & ML Engineering:

• Build, train, and deploy machine learning models across supervised, unsupervised, and reinforcement learning paradigms, selecting the right approach based on business need and data characteristics.
• Apply advanced techniques including natural language processing (NLP), computer vision, and time-series forecasting for domain-specific use cases. Models may include risk forecasting, demand forecasting, inventory optimization and equipment failure predictions.
• Implement model governance processes: versioning, audit trails, model explainability, and responsible AI practices. Apply responsible AI practices: fairness, bias mitigation, ethical considerations.
• Experience in containerization with tools such as Docker, Kubernetes for model deployment and scaling.
• Ability to monitor for model drift detection, performance monitoring, logging and observability.
• Integrate ML systems into broader data ecosystems, ensuring seamless interaction with data warehouses, APIs, and operational systems.
• Translate models into measurable client value.

Collaboration & Communication:

• Proven ability to collaborate effectively with cross-functional teams to understand business requirements and translate them into technical solutions.
• Foster a collaborative and positive team environment, contributing to team success.
• Proven ability to explain complex concepts to non-technical collaborators.
• Ability to work with clients to ensure smooth and successful implementation, delivery and deployment of ML/AI solutions and other relevant data solutions.
• Communication and collaboration: Excellent verbal and written communication skills.

Client Engagement & Delivery

• Le