AI Engineer / Data Engineer (Indianapolis, IN / Onsite)

Moser Consulting • Indianapolis, IN

7d • Hybrid

About The Position

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 (depending on client content) 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.

Requirements

• Communication and collaboration: Excellent verbal and written communication skills.
• A solid understanding of statistical analysis, data modeling and data visualization techniques.
• Excellent time management and organizational skills.
• Advanced proficiency in SQL; expertise in performance tuning and optimization of SQL queries required.
• Strong understanding of ETL/ELT fundamentals and orchestration tools.
• Familiarity with data preprocessing, feature engineering, and model evaluation techniques.
• Proficiency in Python and SQL with strong grounding in data structures and software fundamentals.
• Strong understanding of software engineering practices including version control, testing, module design, and code clarity.
• Expertise in ML, MLOps, and applied AI in production environments.

Nice To Haves

• Bachelor's, Master's, or Ph.D. degree in Computer Science, Data Science, or a related field.
• Minimum 3 - 5 years of experience working with Machine Learning models.
• Must be able to operate effectively in secure, high-compliance, or limited-tooling environments (e.g. no code assistants, on-prem pipelines, locked-down VMs).
• Demonstrated ability to adapt quickly to new technology stacks and client-specific coding standards.
• Working knowledge of ML frameworks and libraries, such as: PyTorch, TensorFlow, and scikit-learn.
• Analytical mindset: Strong problem-solving skills, with the ability to analyze complex data and derive actionable insights.
• History of designing idempotent data workflows that can gracefully handle failures and restarts without data duplication or corruption.
• Proven expertise in at least one major cloud platform (AWS, Azure, Snowflake or GCP) utilizing services for compute, data warehousing.
• History in leverage enterprise platforms (e.g., AI Foundry or similar) to securely containerize and deploy models, ensuring robust endpoint protection, managed identity access, and compliance with organizational security standards.
• Relevant Certifications are beneficial.

Responsibilities

• 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.
• Responsibilities will include debugging, performance tuning, and 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.
• Tasks may involve evaluating tradeoffs among tools, architectures, and modeling approaches.
• Leveraging SQL and python data tooling 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 (defining, maintaining), and automated testing to ensure reliability.
• Documentation will include diagrams, reasoning, assumptions, and operational instructions.
• Work closely w/ a technical lead or senior consultant to align execution with architectural direction and best practices.
• Proven ability to collaborate effectively with cross-functional teams to understand business requirements and translate them into technical solutions.
• Proven ability to foster a collaborative and positive team environment, contributing to team success.
• Proven ability to explain complex concepts to non-technical collaborators.
• Proven ability to break down requirements into clear actionable steps.
• Ability to work with clients to ensure smooth and successful implementation, delivery and deployment of AI/ML and other relevant data solutions.
• Communication and collaboration: Excellent verbal and written communication skills.

Benefits

• Training Opportunities: We believe in lifelong learning and provide numerous avenues for skill enhancement.
• Fully Invested 401K Plan: We help secure your future with a fully invested 401K plan.
• PPO and HDHP Medical Plans: Choose the health insurance program that best fits your needs.
• Employer-Paid Dental and Vision Plans: We cover dental and vision plans, ensuring our employees have access to comprehensive health care.
• Onsite Fitness Center: Stay fit and healthy with our state-of-the-art fitness center.
• Wellness Program: We promote a healthy lifestyle with our wellness program.
• Catered Lunches: Enjoy delicious catered lunches regularly.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 51-100 employees