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Machine Learning Engineer Opt Jobs in Kentucky (NOW HIRING)

$160 - $240/hr

About The Role We are looking for a Machine Learning Engineer to join the ML - Document Intelligence team to drive the design and development of our core Document Intelligence Platform as a Service.

$150 - $210/hr

The Role As a Machine Learning Engineer in computer vision, you will own vision work from data and baseline design through training, error analysis, model export, runtime profiling, and pilot ...

$140 - $220/hr

... engineer, or AI/ML researcher in any domain Demonstrated ability to lead, advise, and provide direction to subordinate team. Experience with and understanding of machine learning and artificial ...

Posted today

$325 - $397/hr

... Machine Learning Engineer who can drive further innovation. About the Role The person in this role will leverage their technical skills, business intuition, and analytical thinking to build best-in ...

Posted today

$140 - $190/hr

As a Senior Machine Learning Operations Engineer you'll be embedded in a team of talented data scientists and software engineers to create sophisticated models that answer hard questions centered ...

New

$266 - $372/hr

As a Senior Staff Machine Learning Engineer, Feed Relevance , you'll drive the development of GenAI ... You will have the opportunity to opt out of recording, transcription and summarization prior to any ...

New

$140 - $200/hr

JOB OVERVIEW General Mills is looking for a Lead ML Engineer. In this role, you are a technical lead within the AIA team focused on delivering the migration of machine learning-based solutions and ...

Posted today

$185 - $278/hr

Applied Machine Learning Engineer, Platform Architecture Cupertino, California, United States Machine Learning and AI Join the SoC Architecture team building ML and generative AI systems that shape ...

Posted today

$140 - $170/hr

Hands-on machine learning and model training experience, including pre-training, mid-training, and ... Authorization to work in the United States; visa transfers, including OPT and H-1B transfers, are ...

Posted today

$140 - $210/hr

Where You Fit We are seeking Machine Learning Engineers (Applied Research & Model Development) to join our team and tackle unique machine learning challenges to advance medicine and improve patient ...

$180 - $270/hr

Serve as the team's machine learning authority, communicating complex model trade-offs to leadership and cross-functional teams to translate technical research into practical, scalable engineering ...

New

$184 - $357/hr

GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve ... We are now looking for an extraordinary Senior Perception Engineer to develop and productize NVIDIA ...

Posted today

$185 - $325/hr

Sr. Machine Learning Engineer, Foundation Models Inference - Cloud OS & Inference Santa Clara, California, United States Machine Learning and AI We are the Foundation Model Inference team within ...

New

$150 - $230/hr

Partner with engineering teams to implement and test models in production environments What we're looking for * PhD in computer science, machine learning, mathematics, physics, statistics, or a ...

New

$120 - $150/hr

Are you passionate about improving the way Machine Learning systems are developed, deployed, and ... You'll work at the intersection of engineering and data science, playing a key part in shaping how ...

Posted today

$180 - $260/hr

Weave is looking for a Staff GenAI Engineer to join the Machine Learning Team specialised in voice and audio modalities , where you will be at the forefront of enabling product innovation and ...

Posted today

$180 - $240/hr

Weave is looking for a Staff GenAI Engineer to join the Machine Learning Team specialised in voice and audio modalities, where you will be at the forefront of enabling product innovation and building ...

$129 - $195/hr

We have a variety of opportunities for software engineers, data scientists, and machine learning engineers. Responsibilities may include: * Support our business partners and optimizes the customer ...

New

Showing results 41-60

Machine Learning Engineer Opt information

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

What are some common challenges machine learning engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

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 a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

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

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

What cities in Kentucky are hiring for Machine Learning Engineer Opt jobs?

Cities in Kentucky with the most Machine Learning Engineer Opt job openings:

Machine Learning Engineer III - Document Intelligence

Jobzhr

On-site

$160 - $240/hr

Other

Posted 6 days ago


Job description

Your work days are brighter here.

We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too.

About The Team

This is a very exciting opening in the AI Platform team in our Document Intelligence team. We believe if you do what you love, you’ll love what you do. There’s a lot to love at Workday. We are part of a global, high‑growth technology company and our team has the opportunity to develop the next generation of Workday’s groundbreaking collaborative products supporting a customer base of more than 31 million strong. Over 65% of the Fortune 500 are Workday customers.

The Document Intelligence team builds AI/ML‑powered solutions to extract actionable insights from unstructured documents. We design scalable document processing pipelines that can ingest and interpret large volumes of data with minimal manual intervention. Our work includes advanced document parsing using NLP, computer vision, and large language models (LLMs), along with in‑house model training for entity resolution. We integrate seamlessly with business workflows for areas like financials, spend management, and more. By continuously evolving our models to handle new document types and edge cases, we help automate and accelerate critical business processes across the organization.

Workday’s AI Platform organization is bringing “AI first” products to life at every step of the Workday product offering. We’re looking for highly creative, results‑focused, and deeply skilled Machine Learning Engineers/scientists to work with us on a range of these challenges.

About The Role

We are looking for a Machine Learning Engineer to join the ML - Document Intelligence team to drive the design and development of our core Document Intelligence Platform as a Service. In this role, you will work on building and optimizing critical features like generic document entity extraction, entity resolution, and document classification, leveraging cutting‑edge AI/ML techniques.

Your primary focus will be to:
  • Support the design and implementation of LLM‑based technologies for document parsing, entity extraction, and classification tasks.
  • Apply traditional ML and deep learning techniques to continuously enhance the accuracy, efficiency, and scalability of our document intelligence models.
  • Build scalable ML pipelines and services for data preprocessing, feature engineering, training, and inference, enabling high‑volume document processing workflows.
  • Perform exploratory data analysis (EDA) on diverse document datasets to uncover valuable insights, optimize feature engineering, and inform model development.
You will also:
  • Collaborate with software engineers, Workday app developers, product managers, and other ML teams
  • Take ownership for finding creative solutions that move projects forward
  • Write clean, maintainable, and testable code following best practices in software engineering, including automation, observability, and scalability.
  • Conduct code reviews, participate in design discussions, and engage in collaborative team activities like hackathons and knowledge‑sharing sessions.
About You

Basic Qualifications:

  • Deep Technical ML Capability: 3+ years of experience researching, developing and deploying production‑grade ML systems, including expertise in deep learning, NLP, Information Retrieval, and recommender systems using frameworks like PyTorch or TensorFlow.
  • Generative AI & Agentic Systems: Proven track record of building and evaluating NLP and LLM‑powered products, including expertise in RAG architectures, agentic frameworks (e.g., LangChain/LangGraph), and long‑context LLM applications (e.g., Text-to‑SQL).
  • Engineering Excellence: 2+ years of Python experience with a focus on modular library design, asynchronous patterns, and scalable system architecture (state management/error handling) for non‑deterministic AI outputs.
Other Qualifications
  • Academic Foundation: Advanced degree (Master’s or Ph.D.) in a quantitative field or a strong portfolio of peer‑reviewed research publications.
  • Optimization & Advanced Techniques: Proficiency in techniques like DSPy, Reinforcement Learning, imitation learning, graph neural networks, multi‑modal models, and large‑scale data processing (PySpark, SQL).
  • Experimental Rigor: A “test‑everything” mindset with experience in A/B testing, Knowledge Graphs, and “Golden Dataset” curation for model benchmarking.
  • Data Pipelines: Proficiency in large‑scale data processing (PySpark, SQL).
  • Production MLOps: Hands‑on experience with the full ML lifecycle, including model fine‑tuning (PEFT), evaluation frameworks (e.g., DeepEval/RAGAS), and cloud‑native deployment (Docker/K8s, AWS/GCP).
  • Collaborative Leadership: Demonstrated ability to lead cross‑functional teams, mentor junior engineers, and solve ambiguous problems with high autonomy.
Workday Pay Transparency Statement

The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role‑specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday’s comprehensive benefits, please click here.

Primary Location: USA.CA.Pleasanton

Primary Location Base Pay Range: $160,000 USD - $240,000 USD

Additional US Location(s) Base Pay Range: $136,200 USD - $240,000 USD

Our Approach to Flexible Work

With Flex Work, we’re combining the best of both worlds: in‑person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in‑office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you’ll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.

Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records.

Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.

At Workday, we are committed to providing an accessible and inclusive hiring experience where all candidates can fully demonstrate their skills. If you require assistance or an accommodation at any point, please email accommodations@workday.com.

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