AI Engineer​/Data Engineer; Indianapolis, IN​/Onsite

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.

We are seeking an AI/ML/Data engineer with several years of technical experience building production‑grade solutions. This role blends AI/ML engineering, data engineering, and software engineering to support clients across a variety of industries. You will deliver within cloud, on‑prem, or hybrid environments to engineer, deploy, and maintain end‑to‑end AI/ML systems. You will collaborate with a technical lead, engineers, analysts, and domain stakeholders while building reusable patterns and contributing to a growing Data Intelligence capability.

• Design, implement and deploy production‑grade machine learning models and systems using modern MLOps practices. Deliverables will span from classical ML to Gen AI.
• Prepare datasets, feature pipelines, evaluation scaffolding, experiment tracking, and model packaging.
• Implement model inference services, deployment workflows and monitoring mechanisms.
• Projects may range from data ingestion and transformation to model serving and application integration.
• Debug, perform performance tuning, and conduct failure analysis across data and model layers.
• Collaborate with domain experts to translate analytical requirements into highly performant ML services and reusable solution patterns.
• Implement model governance and reproducibility standards, ensuring models are versioned.

• Build ingestion, transformation, and storage pipelines for analytical and ML workflows.
• Ensure data quality and integrity by implementing data validation and cleansing processes.
• Evaluate trade‑offs among tools, architectures, and modeling approaches.
• Leverage SQL and Python data tooling to develop scalable, optimized ETL/ELT pipelines to ingest, transform and load large complex datasets from disparate sources (batch and streaming), streamlining for low latency, high throughput and cost‑efficiency.

• Write modular, testable and maintainable codebases that follow idiomatic patterns.
• Build APIs, services and components that integrate models into applications.
• Use containers, CI/CD and automated testing to ensure reliability.
• Document with diagrams, reasoning, assumptions and operational instructions.

• Work closely with a technical lead or senior consultant to align execution with architectural direction and best practices.
• 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.
• Explain complex concepts to non‑technical collaborators.
• Break down requirements into clear actionable steps.
• Work with clients to ensure smooth and successful implementation, delivery and deployment of AI/ML and other relevant data solutions.
• Excellent verbal and written communication skills.