What you’ll do

Become part of an iconic brand that is set to revolutionize the electric pick-up truck & rugged SUV marketplace by achieving the following:

• Install, configure, and maintain AI platform and tools.
• Design, deploy, and operate infrastructure supporting ML and LLM workloads.
• Build, containerize, and deploy AI services using Docker.
• Build and maintain Machine Learning CI/CD pipelines for training, testing, and deployment.
• Deploy and manage AI services across cloud and on-prem environments.
• Automate infrastructure provisioning using Terraform and Infrastructure-as-Code best practices.
• Monitor system performance, reliability, and scalability of AI platforms.
• Implement observability for agentic AI systems to ensure reliability, transparency, and debuggability.
• Perform regular security updates, patching, access control, and vulnerability remediation.
• Integrate AI tools with APIs, data platforms, and internal systems.
• Research, evaluate, and prototype new AI, LLM, and MLOps tools.
• Troubleshoot infrastructure, data, and deployment issues.
• Research, test, and prototype emerging AI technologies.
• Document system architecture, deployment processes, and operational runbooks.

Location & Travel Expectations:

• This role is based out of the Scout Motors corporate headquarters in Charlotte, NC.
• This role requires 4-5 days per week in the office, with regular in-person meetings and events. 
• Applicants should expect that the role will require the ability to convene with Scout colleagues in person and travel to participate in events on behalf of the company from time to time.

What you’ll bring 

We expect all Scout employees to have integrity, curiosity, resourcefulness, and strive to exhibit a positive attitude, as well as a growth mindset. You’ll be comfortable with change and flexible in a fast-paced, high-growth environment. You’ll take a collaborative approach to achieve ambitious goals. Here's what else you'll bring: 

• Bachelor's degree in computer science, information technology, or related field or equivalent work experience.
• 7+ years Practical experience with LLM platforms, LLMOps, and MLOps.
• Experience deploying and maintaining AI or data platforms in production.
• Hands-on experience with AI/automation tools.
• Experience designing and orchestrating agentic automation workflows.
• Strong experience with Terraform and Infrastructure-as-Code.
• Proven experience deploying applications using Docker (Docker files, image optimization, container lifecycle).
• Expertise with cloud platforms such as AWS.
• Expertise with CI/CD tooling (GitHub Actions, GitLab CI).
• Strong Knowledge of Kubernetes and orchestration.
• Solid understanding of networking.
• Experience supporting high-availability, production AI systems.
• Scripting skills (Python, PySpark, Bash).
• Knowledge of security best practices, patch management, and access controls.
• Collaborate with engineering, data, and product teams to support AI initiatives.
• Excellent problem-solving and troubleshooting skills. When a problem occurs, you run towards it not away.
• Effective communication and collaboration skills. You treat colleagues with respect. You have a desire for clean implementations but are also humble in discussing alternative solutions and options.
• A teaching and coaching approach to guiding engineers and teams in approaches.
• Minimum of High School Diploma, GED or equivalent required for all roles at Scout Motors, Inc.

What you'll gain

The benefits of joining Scout include the chance to build products and a company from the ground up.  This is a chance to create something new and lasting – with an iconic brand at its foundation.  In addition, Scout provides competitive compensation and benefits to support your physical, mental, and financial wellbeing. Program specifics are detailed in company policies and employee benefit guides, select highlights:

• Competitive insurance including:
  • Medical, dental, vision and income protection plans
• 401(k) program with:
  • An employer match and immediate vesting
• Generous Paid Time Off including:
  • 20 days planned PTO, as accrued
  • 40 hours of unplanned PTO and 14 company or floating holidays, annually
  • Up to 16 weeks of paid parental leave for biological and adoptive parents of all genders
  • Paid leave for circumstances related to bereavement, jury duty, voting time, or military leave

Pay Transparency

This is a full-time, exempt position eligible to receive a base salary and to participate in an annual performance bonus program. Final salary offered will be determined based on factors including but not limited to the candidate's skills and experience. The annual performance bonus program is preset and not candidate dependent.

Initial base salary range = $140,000.00 - $170,000.00

Internal leveling code: IC8

Shopmonkey's vision is to help every shop thrive by equipping them with the tools they need to run and grow their business. Our cloud based all-in-one shop management software takes owners and technicians from quote to cashing out a satisfied customer. Our software has a modern and intuitive UI and our backend is powered by the latest technologies so our clients can focus on the things they do best. As a Senior ML Engineer at Shopmonkey, you will be a part of a globally distributed engineering team working closely with your product and design counterparts. You will have the chance to work on the frontier of ML modeling, data pipelines, MLOps, and agentic AI systems to meet real-world auto shop needs. Shopmonkey has the structured data, workflows, and operational maturity to deliver ML powered systems that are not only intelligent but trusted and useful. You’ll move fast to bring ML systems from discovery all the way through production, helping to shape the future of the automotive care experience. For any Bay area based candidates, this would be hybrid with 2-3 days/week office at our Morgan Hill, CA office for collaboration. 

What you will do:

• Design, build, and ship production-ready ML models across a range of problem spaces: regression, classification, clustering, ranking, and recommendation systems.
• Conduct end-to-end development of ML systems: data gathering, experimentation, feature engineering, model training, evaluation, deployment, and monitoring.
• Define and track model performance metrics, run A/B tests, and iterate based on real-world feedback.
• Help design and implement shared feature stores so that reusable features can serve multiple models consistently in both batch and real-time contexts.
• Work within a modern MLOps environment to ensure scalable and reliable deployment of models.
• Contribute to training infrastructure, model versioning, and CI/CD pipelines for ML workflows.
• Work closely with data scientists and data engineers to develop data driven solutions that are high impact for businesses.
• Translate complex ML workflows into digestible updates for cross-functional stakeholders.
• Contribute to backlog velocity by owning appropriate tickets and delivering high-impact work in a collaborative, fast-paced environment.
• Implement NLP and LLM-powered components for sentiment analysis, real-time conversation evaluation, and behavior optimization.
• Contribute to analytics and predictive features such as no-show prediction and sentiment dashboards.
• Help build and ship AI agents that help automate key auto-shop business processes.

We are looking for people who have:

• Minimum of 5+ years of industry experience in applied machine learning; advanced degrees (Master’s or PhD) may offset years of experience.
• Proven experience shipping models into production (not just proof-of-concepts or notebooks).
• Proficiency in Python; experience with ML frameworks like PyTorch or Tensorflow.
• Strong foundations in classical ML/DL. Including some of the following: regression, classification, clustering, ranking, feature engineering, model evaluation, and experimentation.
• Bachelor’s degree in a STEM field, or equivalent practical experience.
• Strong collaboration and communication skills—comfortable working with PMs, designers, engineers and other cross functional team members.

Nice to have:

Candidates should have some experience in one or more of the following areas.

• Understanding of MLOps principles: model versioning, orchestration, evaluation, monitoring, model serving, and CI/CD for ML. 
• Understanding of MLOps, and experience with modern tooling like MLFlow, DVC, Airflow, etc.
• Experience with LLMs and NLP frameworks (e.g., TensorFlow, Hugging Face, LangChain).
• Experience with/interest in LLM workflows and agentic workflows
• Cloud infrastructure experience, (e.g. GCP, AWS).
• Familiarity with vector databases (e.g. Pinecone, pgvector) and embedding-based retrieval or similarity search.
• Strong SQL skills for working with large-scale data.
• Experience designing or contributing to feature stores (e.g. Feast, VertexAI Feature Store, Tecton) for shared, reusable feature pipelines.

Bonus Points:

• Prior experience working at a high growth startup.
• Experience building consumer-facing agents in vertical SaaS, in the automotive industry (business or consumers).
• Background in data processing or real-time analytics.
• Experience with Snowflake or other large-scale data warehouse solutions.

In the United States, the range is typically a salary of $165,000 to $200,000 + bonus + equity + benefits. The range provided is Shopmonkey’s reasonable estimate of the base compensation for this role. The actual amount will be based on job-related and non-discriminatory factors such as location, experience, training, skills, and abilities. Consult with your Recruiter during the initial call to determine a more targeted range based on these job-related factors. In addition to this base compensation company stock options and benefits as outlined below are included.

Joining Collibra’s Artificial Intelligence team

We are looking for an experienced AI Engineer who will design and deliver Artificial Intelligence solutions that improve our customers' experience and enable informed, data-driven decision making. We seek someone excited about working with cutting-edge technologies to build pragmatic, performant AI solutions. You'll collaborate with a team of outstanding builders around the world, characterized by a love for innovative technology, a desire to solve problems, and a continuous pursuit of building simple, elegant products that delight customers and simplify all levels of data engagement. You will work primarily with Data Scientists, other AI Engineers, and Machine Learning Operations Engineers, as well as teams across Collibra.

This is a hybrid role based in our Raleigh office. Our hybrid model means you’ll work from the office at least two days each week. This setup helps us stay connected, work more closely together, and keep making progress as a team.

AI Engineers at Collibra are responsible for

• Monitoring of the larger AI/ML landscape, including emerging techniques and current state-of-the-art approaches 
• Transforming prototypes into pragmatic, production-ready solutions which solve impactful business problems
• Creating, operationalizing, and supporting AI/ML models and visualizations to power actionable value and insights
• Evaluating algorithmic results for quality, adaptability, and efficiency
• Contributing to evolving our platforms for Artificial Intelligence and Machine Learning capabilities in support of Collibra’s data products
• Collaborating with cross-functional teams and mentoring junior engineers on AI best practices

You have

• 5+ years of experience delivering production-grade AI/ML projects related to business functions, incorporating advanced techniques (e.g., LLM-based applications, RAG systems, NLP, neural networks, recommendation engines)
• Experience with SQL and relational databases, query authoring as well as working familiarity with a variety of databases (e.g., time series, graph, vector)
• Built and deployed production code in Python with associated AI modules (LangChain, LangGraph, Pandas, Numpy, Tensorflow, etc.)
• Experience with model evaluation, testing frameworks, and validation methodologies
• This position is not eligible for visa sponsorship
• A bachelor’s degree or equivalent related working experience is required

You are

• Deeply technical, driven, and analytical about the insights data can deliver
• Able to cut through hype and noise to identify foundational problems and build maintainable, performant solution
• Passionate about the mathematical principles powering the Generative AI revolution and how to drive sustainable value from LLMs and other GenAI technologies
• Experienced supporting diverse stakeholders and working with cross-functional teams in dynamic environments
• A clear communicator who can explain complex technical concepts to both technical and non-technical audiences
• Product-minded with empathy for end users—you consider how people will actually interact with AI features, not just technical sophistication
• Eager to both learn from others and share knowledge ; AI is evolving rapidly and no one has all the answers

Reporting to Collibra’s Senior Manager of AI Engineering, measures of success are

• Within your first month, you will familiarize yourself with the existing data platform and data products by diving into the architecture, existing products, and the Collibra platform ecosystem
• Within your third month, you will start to deliver new AI/ML features into our SaaS platform
• Within your sixth month, you will operationalize AI products into production environments and contribute to our AI roadmap

Compensation for this role

The standard base salary range for this position is 152,000 - 190,000 per year. This position is not eligible for additional commission-based compensation. Salary offers are based on a combination of factors, including, but not limited to, experience, skills, and location.

In addition to base salary, we offer a competitive total rewards package, including bonus potential, equity for eligible roles, a Flex Fund monthly stipend, pension/401k plans, and more.

CSQ127R318

As a Big Data Solutions Architect (Resident Solutions Architect) in our Professional Services team you will work with clients on short to medium term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data. RSAs are billable and know how to complete projects according to specification with excellent customer service. You will report to the regional Manager/Lead.

The impact you will have:

• You will work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of  professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• You will work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps 
• Design and deployment of performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time
• Databricks Certification

CSQ227R87

Candidates located anywhere within the Central or Eastern Time Zones are also eligible for consideration for this role.

As a Senior Big Data Solutions Architect (Sr Resident Solutions Architect) in our Professional Services team you will work with clients on short to medium term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data. RSAs are billable and know how to complete projects according to specification with excellent customer service. You will report to the regional Manager/Lead.

The impact you will have:

• You will work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap hands-on projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• You will work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• 9+ years experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Apache Spark™ runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps
• Capable of design and deployment of highly performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Experience in building scalable streaming and batch solutions using cloud-native components
• Travel to customers up to 20% of the time
• Nice to have: Databricks Certification