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Machine Learning Engineer Jobs in Pikeville, KY (NOW HIRING)

Comfort building data capabilities from the earliest stages through rapid growth, including interfacing closely with data engineering and machine learning * Experience with data visualization tools ...

New

Patient Care Specialist

Pikeville, KY ยท On-site

$17 - $21.75/hr

Fior & Gentz, an innovative developer of neuro orthotics; and College Park, creators of custom ... Continuous learning through e-learning, training, and language courses * A "you" culture where ...

Patient Care Specialist

Pikeville, KY ยท On-site

$17 - $21.75/hr

Fior & Gentz, an innovative developer of neuro orthotics; and College Park, creators of custom ... Continuous learning through e-learning, training, and language courses * A "you" culture where ...

Machine Learning Engineer information

See Pikeville, KY salary details

$29.9K

$122.2K

$183.6K

How much do machine learning engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for machine learning engineer in Pikeville, KY is $122,186.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,300.00 and $147,100.00 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 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 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 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 are the most commonly searched types of Machine Learning Engineer jobs in Pikeville, KY?

The most popular types of Machine Learning Engineer jobs in Pikeville, KY are:

What cities near Pikeville, KY are hiring for Machine Learning Engineer jobs?

Cities near Pikeville, KY with the most Machine Learning Engineer job openings:

Infographic showing various Machine Learning Engineer job openings in Pikeville, KY as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 24% Part Time, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $122,186 per year, or $58.7 per hour.

VPP-83 - AI Solutions Architect United States - Hybrid (Chicago or Houston Office) (Northern)

Vekend, Llc

Eastern, KY โ€ข On-site

$46.50 - $61.25/hr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 3 days ago

New


Job description

As a Forward Deployed Engineer, you will operate at the front lines of innovation embedded directly with subject matter experts, product, and engineering teams to rapidly design, architect, prototype, and deploy solutions that solve high-priority business problems. You will be expected to go from concept to working prototype in days, not months, while maintaining enterprise-grade standards for quality, security, and scalability. You bring an exceptional combination of skills: deep hands-on engineering experience across AI agents and full-stack development, and the interpersonal skills to earn trust, drive alignment, and influence without authority. You are equally comfortable whiteboarding a system architecture with senior stakeholders and writing production code the same afternoon. You thrive in fast, ambiguous environments where creative thinking and execution speed matter.

Department:

Contact Center

Project Location(s):

United States - Hybrid (Chicago or Houston Office)

Job Type:

Employee

Education:

Bachelor's

Who Youโ€™ll Work With

We are seeking an experienced AI Solutions Architect to lead the design, development, and deployment of next-generation AI and Generative AI solutions within enterprise Contact Center environments. This role will be responsible for architecting intelligent customer experience solutions that leverage Large Language Models (LLMs), Agentic AI, Conversational AI, Retrieval-Augmented Generation (RAG), predictive analytics, and cloud-native technologies to improve customer satisfaction, agent productivity, and operational efficiency.

The ideal candidate combines deep AI/ML expertise with hands-on experience supporting Contact Center platforms, customer service operations, conversational AI, workforce optimization, and customer experience transformation initiatives.

What Youโ€™ll Do
  • Architect and deliver end-to-end AI and Generative AI solutions supporting Contact Center and Customer Experience (CX) organizations.
  • Design and implement intelligent virtual agents, AI-powered agent assist capabilities, knowledge management solutions, and automated customer interaction workflows.
  • Develop RAG-based applications, conversational AI platforms, multi-agent systems, and LLM-powered customer support solutions.
  • Partner with Contact Center leaders, operations teams, and business stakeholders to identify opportunities for AI-driven automation and process optimization.
  • Create AI solutions to improve call deflection, first-call resolution, customer sentiment analysis, agent productivity, quality monitoring, and root cause analysis.
  • Design scalable cloud architectures supporting high-volume customer interactions across voice, chat, email, and digital channels.
  • Lead development of predictive analytics models for customer behavior, churn prediction, workforce planning, and operational forecasting.
  • Establish AI governance, MLOps frameworks, model monitoring, and responsible AI best practices.
  • Collaborate with engineering teams to develop streaming and batch data pipelines supporting real-time customer engagement use cases.
  • Present solution architectures, business cases, and AI transformation strategies to executive and senior leadership teams.
  • Create reference architectures, technical standards, and implementation roadmaps for enterprise AI adoption.
  • Provide technical leadership and mentorship to data scientists, engineers, architects, and business teams.
What Youโ€™ll Bring
  • Bachelorโ€™s degree in Computer Science, Engineering, Information Systems, or related technical discipline.
  • 10+ years of experience in AI/ML, Solution Architecture, Data Analytics, Cloud Architecture, or Customer Experience technologies.
  • Proven experience architecting and deploying enterprise AI and Generative AI solutions.
  • Experience supporting Contact Center, Customer Experience, Customer Service, or Customer Operations organizations.
  • Strong understanding of customer service workflows, knowledge management, conversational AI, and customer engagement strategies.
  • Experience designing solutions utilizing LLMs, RAG architectures, Agentic AI, and conversational AI technologies.
  • Hands-on experience with machine learning frameworks and cloud AI services.
  • Experience working with executive stakeholders and driving large-scale digital transformation initiatives.
  • Strong communication and stakeholder management skills.
Nice-to-Haves
  • Experience with Contact Center platforms such as Genesys, NICE CXone, Five9, Amazon Connect, Cisco Contact Center, or similar technologies.
    Google Cloud Professional Machine Learning Engineer certification or equivalent cloud certification.
  • Experience implementing AI-powered agent assist, quality monitoring, call summarization, or customer analytics solutions.
  • MBA or advanced degree focused on Business Analytics, Data Science, Innovation, or Technology Management.
  • Experience within telecommunications, customer service, customer operations, or enterprise technology environments.
What Makes Us Great Place To Work

Vekend is a people-first organization focused on developing thoughtful products and services that create meaningful impact for our customers and communities. We are committed to fostering a collaborative, respectful, and inclusive work environment where employees are empowered to take ownership of their work, contribute ideas, and grow professionally. We strive to support flexibility and work-life balance while maintaining high standards of performance and accountability.

What Makes Us Great Place To Work

For all locations, the good-faith, reasonable annualized full-time compensation for this role will be determined based on competitive market data and may vary depending on geographic location, job-related knowledge, skills, experience, education, and other business considerations. Specific compensation details will be discussed during the interview process.,Vekend offers a comprehensive benefits and wellness package designed to support employeesโ€™ overall well-being, financial security, and professional growth. Eligibility and coverage are subject to the terms of the applicable benefit plans and company policies.,Eligible employees have access to medical, dental, and vision insurance with company contributions toward premiums, a 401(k) retirement plan with company matching, and Paid Time Off that begins accruing on the first day of employment. We also support flexible work arrangements and opportunities for professional growth.,Benefits eligibility, coverage, and company contributions are subject to the terms of the applicable plan documents and may be modified at the companyโ€™s discretion.

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