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Ml Inference Jobs in Indiana (NOW HIRING)

inKind

Data Engineer (AI)

Austin, IN · On-site

$135K - $155K/yr

The position requires working across departments to build, operate, and optimize highly available data pipelines that feed analytics, ML training and inference, and retrieval-augmented generation ...

Crowe LLP

Senior AI Engineer

South Bend, IN · On-site +1

$102K - $140K/yr

Basic ML/AI literacy (training vs inference, knowledge cutoffs, LLM fundamentals) * Prompt engineering and instruction hierarchies * Context window and context management * Model selection and ...

Crowe LLP

Senior AI Engineer

Indianapolis, IN · On-site +1

$99K - $137K/yr

Basic ML/AI literacy (training vs inference, knowledge cutoffs, LLM fundamentals) * Prompt engineering and instruction hierarchies * Context window and context management * Model selection and ...

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Ml Inference information

What is ML inference?

ML inference refers to the process of using a trained machine learning model to make predictions or decisions based on new data. After a model has been trained on historical data, inference is the phase where that model is deployed and used in real-world applications, such as recognizing speech, detecting objects in images, or recommending products. The focus in ML inference is on speed, efficiency, and scalability to ensure quick predictions, often in real time. This process is critical for practical applications like mobile apps, web services, and embedded systems. Optimizing inference involves reducing latency, memory usage, and computational requirements.

What is the difference between Ml Inference vs Data Scientist?

AspectML InferenceData Scientist
Required CredentialsKnowledge of machine learning models, programming skillsDegree in data science, statistics, or related fields
Work EnvironmentDeploying models in production, real-time data processingData analysis, model development, research
Industry UsageAI product deployment, software companiesResearch institutions, tech firms, consulting

ML Inference focuses on deploying trained models to make predictions on new data, often in real-time. Data Scientists develop and analyze models, working primarily in research and development. While both roles require understanding of machine learning, ML Inference emphasizes deployment and operationalization, whereas Data Scientists focus on model creation and analysis.

Which 3 jobs will survive AI?

For ML Inference roles, jobs that require complex problem-solving, creativity, and emotional intelligence are more likely to persist, such as data scientists, AI ethics specialists, and machine learning engineers. These roles involve tasks that are difficult to automate and often require specialized skills, domain knowledge, and critical thinking. Continuous learning and expertise in AI tools and programming languages like Python or TensorFlow can also enhance job security in this field.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, specialized skills in deep learning, and strong industry demand can earn $500,000 or more annually, especially in high-cost-of-living areas or within top tech companies. Achieving this level typically requires advanced degrees, certifications, and a proven track record of impactful projects.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often requiring advanced skills in deep learning, data science, and experience with tools like TensorFlow or PyTorch. These positions usually involve leadership responsibilities, strategic planning, and may require multiple years of specialized experience or advanced degrees.

Is ML a high paying job?

Machine Learning (ML) inference roles are generally well-paid due to the specialized skills required, such as knowledge of algorithms, programming, and data analysis. Salaries vary based on experience, location, and industry, but they tend to be higher than average for tech positions. Advanced roles often require proficiency with tools like TensorFlow or PyTorch and may include certifications or advanced degrees.

What are some common challenges faced by ML Inference Engineers when deploying models to production?

ML Inference Engineers often encounter challenges such as optimizing model latency and throughput to meet production requirements, ensuring compatibility with diverse hardware environments, and managing model versioning and updates without disrupting service. Additionally, balancing resource utilization and inference accuracy while monitoring real-time performance metrics is crucial. Collaboration with data scientists, DevOps, and software engineers is typically essential to streamline deployment and maintain robust, scalable inference pipelines.

What are the key skills and qualifications needed to thrive in ML Inference, and why are they important?

To thrive in ML Inference, you need a solid background in machine learning principles, programming (Python or C++), and experience with deploying models at scale, often supported by a degree in computer science or a related field. Familiarity with frameworks and tools such as TensorFlow, PyTorch, ONNX, and cloud platforms like AWS SageMaker or Google AI Platform is typically required. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for collaborating with multidisciplinary teams and optimizing model performance. These skills ensure efficient, scalable, and reliable deployment of machine learning solutions in real-world applications.
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What job categories do people searching Ml Inference jobs in Indiana look for? The top searched job categories for Ml Inference jobs in Indiana are:
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Ml Inference jobs near you
AI Engineer / Data Engineer (Indianapolis, IN / Onsite)

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

Moser Consulting

Indianapolis, IN • On-site

$120K - $155K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 14 days ago

Job description

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 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.

Role Responsibilities

Artificial Intelligence / Machine Learning Engineering:

  • 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.

Data Engineering:

  • 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.

Software Engineering:

  • 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.

Collaboration & Communication:

  • 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.
    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.
    Preferred Requirements
    • 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.
    Where You'll Work

    Moser has two offices in Indianapolis, IN, and one in Baltimore, MD. This position requires a hybrid/on-site work schedule. Must be able to work at least 3 days on-site at a local client.

    Salary

    At Moser Consulting, we believe in pay transparency and fairness. The $120k-$155k salary range for this role is not just a numberit's a reflection of the value we place on the skills and experience our employees bring to our team. We are committed to offering a competitive salary that aligns with the industry standards and the unique competencies you bring to our community.

    Benefits

    For over a quarter of a century, Moser Consulting has been a beacon for top-tier IT talent who excel in self-management. Our people are our greatest asset. We don't just hire the bestwe welcome them into our family, connect them with opportunities, and empower them to create innovative solutions to technology challenges.

    Our unique culture is our competitive edge. It fosters happiness, health, and low stress, even in an industry known for its demands. This is why we're consistently recognized as one of the Best Places to Work in Indiana. We provide our employees with an inspiring workspace, a fun and collaborative atmosphere, and a generous compensation package. But that's not all.

    We also offer a suite of benefits designed to support and enrich our employees' lives. These include:

    • 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.

    At Moser Consulting, we don't just offer jobswe offer careers, growth, and a chance to join a thriving community. Come, be a part of our family.

    Moser Consulting is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.