1

Machine Learning Engineer Jobs in Manhattan, KS (NOW HIRING)

Senior Data Platform Engineer

Manhattan, KS · On-site

$104K - $137K/yr

LLMs & Machine Learning: Practical experience integrating LLMs or ML models into production systems - including at least several of: prompt engineering, RAG, embeddings/vector search, tool/function ...

Senior Staff Engineer

Manhattan, KS · On-site

$92K - $127K/yr

Provide engineering and consulting services for a broad array of projects and clients. This may include performing and/or leading field investigations, engineering analysis, calculations, and ...

Senior Staff Engineer

Manhattan, KS · On-site

$88K - $121K/yr

Provide engineering and consulting services for a broad array of projects and clients. This may include performing and/or leading field investigations, engineering analysis, calculations, and ...

Are you a Senior-Level Professional Engineer looking to be part of an organization that prioritizes your growth and well-being, empowering you to lead with innovation and shape the future of ...

Senior Engineer - Municipal Projects

Manhattan, KS · On-site

$92K - $127K/yr

We engineer and design solutions that improve the world around us. As a company, we promise to always be responsive, transparent, and focused on results - for our people, our clients, and our company.

We engineer and design solutions that improve the world around us. As a company, we promise to always be responsive, transparent, and focused on results - for our people, our clients, and our company.

Senior Engineer - Municipal Projects

Manhattan, KS · On-site

$92K - $127K/yr

We engineer and design solutions that improve the world around us. As a company, we promise to always be responsive, transparent, and focused on results - for our people, our clients, and our company.

Machine Learning Engineer information

See Manhattan, KS salary details

$27.9K

$114K

$171.3K

How much do machine learning engineer jobs pay per year?

As of Aug 3, 2026, the average yearly pay for machine learning engineer in Manhattan, KS is $114,014.00, according to ZipRecruiter salary data. Most workers in this role earn between $89,900.00 and $137,200.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What cities near Manhattan, KS are hiring for Machine Learning Engineer jobs? Cities near Manhattan, KS with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Manhattan, KS as of July 2026, with employment types broken down into 93% Full Time, 4% Part Time, and 3% Contract. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution, with an average salary of $114,014 per year, or $54.8 per hour.

Senior Data Platform Engineer

Purple Wave Auction

Manhattan, KS • On-site, Remote

$100K - $125K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 7 days ago


Job description

Description
Build the Data Platform That Powers What's Next.
We're seeking a seasoned Senior Data Platform Engineer to design and operate the pipelines, services, and data products that the rest of the company builds on. In this role, you'll own the flow of data end to end - ingesting and transforming it through ETL/ELT and dbt, orchestrating reliable batch and streaming workflows, and exposing it through the APIs and microservices that product teams depend on, including the next generation of features powered by large language models (LLMs) and machine learning. Beyond hands-on engineering, you'll shape technical direction, mentor teammates, and help drive standardization across the department. If you're energized by building dependable data systems and excited to apply LLMs and ML to real product problems, we'd love to have you on the team.
We are seeking an experienced Senior Data Platform Engineer to join our data team in building and maintaining a robust data platform and the backend services around it, while providing technical guidance and mentorship. This role focuses on designing and shipping high-quality data pipelines and transformations - building and maintaining ETL/ELT and dbt workflows, orchestration, and data-quality and observability practices - alongside the Python microservices and APIs that serve data and integrate LLM and ML capabilities into production. You'll also contribute to technical direction at the team level and lead standardization efforts across the department, collaborating closely with product teams and stakeholders to deliver reliable, scalable, and well-documented data and backend systems.
Responsibilities:
  • Technical Collaboration
    • Contribute to technical direction and strategic planning at the team level.
    • Evaluate and recommend new technologies and approaches for backend and AI/ML evolution.
    • Provide technical guidance and code reviews for team members.
    • Provide technical guidance and support to product teams consuming backend services.
  • Data Pipelines, ETL & Transformation
    • Design, build, and maintain data pipelines and ETL/ELT workflows that ingest, move, and transform data across source systems, the warehouse, and downstream consumers.
    • Develop and maintain dbt models, tests, and documentation to support analytics, reporting, and product features.
    • Build and operate workflow orchestration for batch and streaming data (scheduling, dependency management, retries, and alerting).
    • Establish and enforce data quality, reliability, and observability practices across pipelines (monitoring, lineage, freshness, and validation).
    • Implement schema management, versioning, and migration patterns to evolve data models safely.
    • Optimize pipeline performance, cost, and scalability across the data platform.
  • Data Application Development & Maintenance
    • Design, develop, and maintain microservices in Python; familiarity with Go and/or TypeScript/JavaScript is a plus.
    • Design and build APIs and services that integrate LLMs and ML models - including retrieval-augmented generation, embeddings, prompt orchestration, tool/function calling, and agentic workflows.
    • Develop self-service tools and APIs that enable product teams to independently leverage backend and AI capabilities.
    • Establish patterns for safely, reliably, and cost-effectively operating LLM- and ML-backed features in production (evaluation, observability, guardrails, fallbacks).
    • Build and maintain CI/CD pipelines and deployment automation.
    • Create and maintain technical documentation and standards repositories.
  • Team Collaboration & Process
    • Work within an Agile framework to prioritize and deliver backend improvements.
    • Collaborate with product teams and stakeholders to understand requirements and pain points.
    • Help foster a culture of continuous learning, improvement, and technical excellence.
    • Encourage adoption of consistent tooling and processes across development teams.
    • Contribute to cross-team initiatives to improve developer experience and backend consistency.
  • Undertake additional assigned duties as requested.

Supervisory Responsibilities:
  • None.

Qualifications:
  • Bachelor's degree in Computer Science, Engineering, or a related field, OR 6+ years of professional software development experience in lieu of degree.
  • 5+ years of backend software development experience.
  • 2+ years of experience in technical leadership or mentoring roles.
  • Programming Languages: Expert proficiency in Python; familiarity with Go and/or TypeScript/JavaScript is a plus.
  • LLMs & Machine Learning: Practical experience integrating LLMs or ML models into production systems - including at least several of: prompt engineering, RAG, embeddings/vector search, tool/function calling, evaluation, and cost/latency optimization.
  • Databases: Advanced experience with MySQL, PostgreSQL, and Redis; familiarity with vector databases (e.g., pgvector, Pinecone, Weaviate) is a plus.
  • APIs: Proven experience designing, building, and operating RESTful APIs at scale.
  • CI/CD: Advanced pipeline design and implementation using industry best practices and tools.
  • Infrastructure: Experience with cloud providers (AWS, Azure, GCP); container orchestration experience (Kubernetes) is a plus.
  • Proven experience building and scaling backend services and APIs.
  • Deep understanding of microservice architecture patterns, distributed systems, and best practices.
  • Experience with observability tools and practices (monitoring, logging, tracing) - including for AI/ML workloads where applicable.
  • Strong ability to communicate complex technical concepts to diverse audiences.
  • Strong customer-focused mindset with emphasis on the developer and end-user experience.
  • Experience facilitating technical discussions and building consensus.
  • Demonstrated experience providing technical guidance.
  • Spanish speaking bi-lingual candidates are encouraged to apply.
  • Candidates may be requested to complete position specific skills assessments.
  • Applicants must be either a U.S. Citizen or eligible to work in the U.S.
  • Requires the ability to satisfactorily complete a background check.

Working Settings:
  • Full-time Salaried Exempt, not eligible for overtime.
  • Office hours are 8am-5pm, Monday through Friday, Central Time zone, additional hours may be required depending on priorities.
  • This position is remote work eligible within the United States. Please be aware: the first week of employment includes mandatory in-person training. Remote start arrangements are not available.
  • Also mandatory: One week a year of in-person training with the department.
  • Potential for 10% travel, should the need arise.
  • Prolonged periods sitting at a desk and working on a computer.
  • Must be able to lift up to 15 pounds at times.

Compensation:
  • The salary varies based on experience and qualifications, but typically ranges from $100,000 to $125,000 per year.
  • Monthly Bonus Program - determined by the Company's monthly revenue result and are paid on a "percent to plan" payout formula (90% = $300, 100% = $600, 110% = $900, 120% = $1,200).
  • Monthly phone stipend in accordance with the Company's cell phone policy, currently $120/month.
  • Health, Dental, and Vision insurance.
  • 401(k) plan with an employer match up to 4% starting the first day of employment.
  • Company-paid Life Insurance with options for supplemental coverage.
  • Fully paid Short-Term Disability provided by the Company.
  • 3 Weeks of PTO annually (details shared during onboarding).
  • Employee Stock Purchase Program (ESPP) - Eligible to purchase company stock at a discount after 90 days of employment, with enrollment opportunities each May and November.