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Mlops Contract Jobs in Indiana (NOW HIRING)

Mlops Contract information

What is an MLOps contract?

An MLOps contract refers to a temporary or project-based agreement for professionals who specialize in Machine Learning Operations (MLOps). MLOps combines machine learning, software engineering, and DevOps practices to streamline the deployment, monitoring, and management of machine learning models in production. These contracts typically require expertise in automation, CI/CD pipelines, cloud platforms, and model lifecycle management. Contractors are often hired to help organizations quickly implement or scale their machine learning infrastructure, ensuring models are reliable, scalable, and secure.

What are the key skills and qualifications needed to thrive as an MLOps contract professional, and why are they important?

To thrive as an MLOps Contract professional, you need solid experience in machine learning, software engineering, and cloud infrastructure, often supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, and platforms such as AWS, Azure, or GCP, along with certifications like AWS Certified Machine Learning or Google Professional ML Engineer, is highly valuable. Strong problem-solving, communication, and collaboration skills help you deliver robust solutions and work effectively with cross-functional teams. These skills ensure efficient deployment, scalability, and maintenance of machine learning models in production environments.

What is the difference between Mlops Contract vs Data Engineer?

AspectMlops ContractData Engineer
Required CredentialsCertifications in cloud platforms, scripting, and ML toolsDegree in Computer Science or related field, SQL, Python skills
Work EnvironmentProject-based, contract roles in cloud and ML teamsFull-time or contract, data pipeline development in data teams
Employer & Industry UsageTech companies, startups, consulting firmsLarge enterprises, finance, healthcare, tech
Search & Comparison IntentUnderstanding contract roles in ML operationsData pipeline and infrastructure roles

While both roles involve working with data and cloud tools, Mlops Contract focuses on deploying and maintaining machine learning models in production environments on a contractual basis. Data Engineers primarily build and manage data pipelines and infrastructure. The roles overlap in skills like scripting and cloud familiarity but differ in scope and responsibilities.

What are some common challenges faced by MLOps contractors when integrating machine learning models into existing production systems?

MLOps contractors often encounter challenges such as aligning model deployment processes with an organization's existing infrastructure and ensuring seamless collaboration between data science and engineering teams. They must navigate differences in technology stacks, manage versioning of models and datasets, and address issues related to scalability and monitoring in production environments. Effective communication and a thorough understanding of both machine learning workflows and DevOps practices are key to overcoming these hurdles and delivering reliable, maintainable solutions.
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Senior AI Architect, Indianapolis, IN

Agility 360

Indianapolis, IN • On-site

Full-time, Contractor

Re-posted 22 days ago


Job description

Senior AI Architect, Indianapolis, IN
Agility 360 seeking a Senior AI Architect for a client in Indianapolis, IN. This person will be responsible for shaping enterprise-wide AI architecture and driving scalable, ethical, and high-impact AI solutions. This role requires strong systems thinking, hands-on experience with AI/ML and GenAI technologies, and the ability to translate business needs into practical, production-ready solutions.
ESSENTIAL JOB FUNCTIONS
  • Partner with business leaders, product managers, and stakeholders to understand workflows, constraints, and AI opportunities
  • Assess AI use cases for feasibility, data readiness, architecture impact, and delivery risk
  • Translate business requirements into scalable AI solution architectures and technical designs
  • Design enterprise-grade AI solutions including data flows, integrations, security, and monitoring
  • Develop architecture artifacts such as workflows, diagrams, and decision records
  • Recommend AI approaches (ML, GenAI, RAG, agentic workflows, automation, hybrid models)
  • Ensure solutions meet standards for scalability, reliability, compliance, and responsible AI
  • Collaborate with architecture, security, data, and governance teams to align with enterprise standards
  • Build prototypes, PoCs, and reference implementations to validate solutions and reduce risk
  • Provide hands-on technical guidance, design reviews, and troubleshooting support
  • Mentor engineers and cross-functional teams through coaching and knowledge sharing
  • Establish reusable AI architecture standards, patterns, and best practices
  • Define and promote responsible AI principles including transparency, privacy, and oversight
  • Continuously evaluate emerging AI technologies and incorporate practical innovations
  • Capture lessons learned and develop reusable playbooks and architecture guidance

EDUCATION / EXPERIENCE REQUIREMENTS
  • Bachelor's degree in Computer Science, Data Engineering, or related field required; Master's preferred
  • 10+ years of software engineering or architecture experience with 5+ years in AI/ML solutions
  • Strong expertise in AI/ML system design, MLOps, and cloud-native architectures
  • Experience with LLMs, RAG architectures, vector databases, and modern AI frameworks
  • Hands-on experience with platforms such as AWS SageMaker, Azure ML, Vertex AI, Databricks, or OpenAI APIs
  • Proven ability to lead architecture decisions and collaborate across enterprise teams
  • Knowledge of AI governance, responsible AI practices, and data privacy/security standards
  • Strong communication, organizational, and problem-solving skills
  • Experience with enterprise architecture frameworks (Zachman/TOGAF) preferred
  • Cloud or architecture certifications (AWS, Azure) preferred

ADDITIONAL DETAILS
  • Location: on-site in Indianapolis, IN
  • Contract to hire
  • Salary: Commensurate with experience.