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Ml Inference Jobs in Missouri (NOW HIRING)

Bass Pro Shops

Senior AI Engineer

Springfield, MO · On-site

$95K - $130K/yr

Design, develop, and deploy LLM-based, RAG, agentic AI, and generative AI solutions using modern ML ... and inference optimization techniques. * Integrate AI solutions via APIs and event-driven ...

Nebius

Data Center IT Manager

Kansas City, MO · On-site

$146K - $220K/yr

... AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.

Walmart

Staff, Data Scientist

Anderson, MO · On-site

$110K - $220K/yr

... inference. * GenAI & Agents : Hands-on experience with LLMs, prompt engineering, fine-tuning, and agent orchestration frameworks. * Systems Thinking : Proven ability to design and scale ML pipelines ...

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Ml Inference information

What is a $900000 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 involving advanced skills in deep learning, data modeling, and programming with tools like Python and TensorFlow. These positions usually require extensive experience, specialized knowledge, and may include leadership responsibilities or strategic decision-making.

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.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and expertise in deploying large-scale models can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their specialized knowledge and impact on product development.

Which 3 jobs will survive AI?

Jobs involving Ml Inference, such as data scientists, machine learning engineers, and AI system architects, are likely to persist as they require specialized expertise in developing, deploying, and maintaining AI models. These roles demand critical thinking, domain knowledge, and skills in programming and data analysis that are less easily automated. Continuous learning and staying updated with AI tools and frameworks are essential for these professions to remain relevant.

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.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and optimize AI models and systems. While AI automation tools can assist with certain tasks, MLEs are essential for building, tuning, and maintaining complex models, making complete replacement unlikely in the near term. Their expertise in data handling, model deployment, and system integration remains critical in AI development environments.

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.
What are popular job titles related to Ml Inference jobs in Missouri? For Ml Inference jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Ml Inference jobs in Missouri look for? The top searched job categories for Ml Inference jobs in Missouri are:
What cities in Missouri are hiring for Ml Inference jobs? Cities in Missouri with the most Ml Inference job openings:
Ml Inference jobs near you
Infographic showing various Ml Inference job openings in Missouri as of June 2026, with employment types broken down into 95% Full Time, 4% Part Time, and 1% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution.
Senior AI Engineer

Senior AI Engineer

Bass Pro Shops

Springfield, MO • On-site

$95K - $130K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 3 days ago

Bass Pro Shops rating

6.5

Company rating: 6.5 out of 10

Based on 421 frontline employees who took The Breakroom Quiz

15th of 39 rated national retailers

Job description

POSITION SUMMARY:
We are seeking an Sr AI Engineer to join our Information Technology team at our corporate office in Springfield, MO.
The Sr AI Engineer serves as a senior technical leader responsible for architecting, scaling, and governing enterprise AI platforms and solutions aligned with the enterprise AI roadmap. This role leads the design and operationalization of advanced AI systems, including generative AI, agentic workflows, retrieval-augmented generation (RAG), and intelligent automation capabilities that drive measurable business impact across the enterprise.
This position provides technical leadership across AI engineering initiatives, establishes enterprise AI standards and best practices, mentors engineering teams, and partners closely with business, data, security, and platform leaders to ensure scalable, secure, and production-ready AI ecosystems.
This position requires working onsite in our Springfield, MO headquarters.
ESSENTIAL FUNCTIONS:
  • Lead enterprise AI architecture decisions, reference patterns, and platform strategies across multiple business domains.
  • Collaborate with stakeholders to identify AI-driven automation and insight opportunities and define success metrics/acceptance criteria.
  • Translate business needs into technical requirements and design end-to-end AI workflows, including data sourcing, orchestration, and integration points.
  • Ensure data readiness by assessing availability and quality across enterprise and third-party sources; partner with Data Engineering to design and validate pipelines that produce high-quality, AI-ready datasets with data contracts, lineage, and schema-drift detection.
  • Perform data preparation and transformation in SQL or Python when needed for AI workflows.
  • Conduct data quality assessments, establish validation rules, maintain data lineage and data contracts, and implement schema-drift detection with automated gates.
  • Design, develop, and deploy LLM-based, RAG, agentic AI, and generative AI solutions using modern ML/LLM frameworks and cloud AI services.
  • Contribute to and implement enterprise PromptOps and LLMOps practices including evaluation pipelines, prompt governance, structured outputs, guardrails, rollback strategies, and automated testing.
  • Build and operate autonomous and semi-autonomous AI workflows with auditable actions, human-in-the-loop approvals, feature flags, and operational safeguards.
  • Implement model lifecycle management with experiment tracking, model registry, retraining, embedding/vector-index versioning, rollback, and monitoring.
  • Lead evaluation and selection of foundation models, embedding strategies, vector retrieval architectures, and inference optimization techniques.
  • Integrate AI solutions via APIs and event-driven architectures using versioned, backward-compatible contracts with semantic versioning and deprecation policies.
  • Apply MLOps and LLMOps best practices for scalable, observable, and secure deployments including containerization, orchestration, CI/CD, and model lifecycle management.
  • Implement automated testing including unit, integration, regression, evaluation, and contract testing for AI systems and services.
  • Partner with Data Scientists and engineering teams to productionize AI and ML solutions into scalable enterprise systems.
  • Provide technical mentorship and code/design reviews for AI Engineers, Data Engineers, and software development teams.
  • Ensure responsible AI governance including RBAC/IAM, secrets management, PII minimization/redaction, audit logging, explainability, and compliance with governance and privacy standards.
  • Lead implementation of observability frameworks including tracing, telemetry, hallucination detection, token/cost monitoring, dashboards, and alerting.
  • Establish service-level objectives (SLOs), operational standards, reliability metrics, and incident response processes for AI platforms.
  • Research and evaluate emerging AI technologies such as multimodal models, vector databases, agentic AI, and AI infrastructure platforms.
  • Contribute to AI standards, reusable frameworks, engineering documentation, and enterprise best practices.
  • Participate in on-call rotation and operational support activities as needed.
  • ALL OTHER DUTIES AS ASSIGNED

EXPERIENCE/QUALIFICATIONS:
  • Minimum Degree Required: Bachelor's Degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or related field (or equivalent experience).
  • 5+ years of experience in AI engineering, machine learning systems, distributed systems, or enterprise AI platform development.
  • 3+ years designing and deploying enterprise-scale LLM, RAG, or agentic AI solutions in production environments.
  • Demonstrated experience leading architecture and delivery of scalable AI platforms or mission-critical AI systems.
  • Deep proficiency in Python and modern AI/ML frameworks.
  • Experience deploying LLM/RAG systems with enterprise data including evaluation frameworks, guardrails, and structured-output validation.
  • Strong experience with vector databases, semantic retrieval systems, and embedding optimization strategies.
  • Solid understanding of SQL, data modeling, and data preparation for AI consumption.
  • Experience with major cloud platforms (AWS, Azure, GCP) and enterprise data platforms/warehouses such as Snowflake.
  • Experience with API development, containerization, orchestration platforms such as Kubernetes, and CI/CD automation.
  • Strong understanding of AI governance, security, compliance, and responsible AI practices.
  • Experience mentoring engineers and leading cross-functional technical initiatives.

KNOWLEDGE, SKILLS, AND ABILITY:
  • Strong systems architecture and platform engineering expertise.
  • Ability to lead technical strategy and influence architectural direction across teams.
  • Strong analytical and problem-solving skills with an end-to-end ownership mindset.
  • Ability to translate complex AI concepts into actionable business outcomes.
  • Excellent communication and collaboration skills across technical and business teams.
  • Expertise in designing scalable, resilient, and maintainable AI systems.
  • Proficiency with Git-based version control and collaborative development workflows.
  • Familiarity with Agile methodologies and iterative delivery models.
  • Understanding of AI feasibility, ROI, and value realization within enterprise environments.
  • Experience mentoring engineers and fostering engineering best practices.
  • Commitment to responsible and ethical AI development aligned with company standards.

TRAVEL REQUIREMENTS:
  • N/A

PHYSICAL REQUIREMENTS:
Regularly sits and works on a computer.
Occasionally stands and walks.
Seldom/never lifts up to 50 lbs.
INDEPENDENT JUDGEMENT:
Performs duties within scope of general company policies, procedures, and objectives. Analyzes problems and performs needs assessments. Uses judgment in adapting broad guidelines to achieve desired result. Regular exercise of independent judgment within accepted practices. Makes recommendations that affect policies, procedures, and practices.
Full Time Benefits Summary:
Enjoy discounts on retail merchandise, our restaurants, world-class resorts and conservation attractions!
  • Medical
  • Dental
  • Vision
  • Health Savings Account
  • Flexible Spending Account
  • Voluntary benefits
  • 401k Retirement Savings
  • Paid holidays
  • Paid vacation
  • Paid sick time
  • Bass Pro Cares Fund
  • And more!

Bass Pro Shops is an equal opportunity employer. Hiring decisions are administered without regard to race, color, creed, religion, sex, pregnancy, sexual orientation, gender identity, age, national origin, ancestry, citizenship status, disability, veteran status, genetic information, or any other basis protected by applicable federal, state or local law.
Reasonable Accommodations
Qualified individuals with known disabilities may be entitled to reasonable accommodation under the Americans with Disabilities Act and certain state or local laws.
If you need a reasonable accommodation for any part of the application process, please visit your nearest location or contact us at hrcompliance@basspro.com.
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