Job description

Here at Scout Motors, we're carrying forward the heritage of one of the most iconic American vehicles in history. A vehicle dating back to 1960. One that forged the path for future generations of rugged SUVs and trucks and will do so once again. But Scout is more than just a brand, it’s a legacy steeped in a culture of exploration, caretaking, and hard work. The Scout brand is all about respect. Respect for the past and the future by taking an iconic American brand that hasn’t been around for a while, electrifying it, digitizing it, and loading it with American innovation. Respect for communities by creating a company that stands for its people and its customers. Respect for both work and play, with vehicles that are equally at home at a camp site, a job site, or on a Tuesday commute. And respect for our customers by developing two powertrains that meet their requirements — an all-electric powertrain as well as the Harvester™ range extender powertrain which includes a built-in gas-powered generator with an estimated 500 miles of combined range. At Scout Motors, we empower our talented, inclusive, and entrepreneurial teams to innovate. What makes a Scout employee? Someone who is a visionary and a leader, who seeks new paths and shares lessons learned. A knowledgeable doer who collaborates across the company to build better. A go-getter with unrivaled passion. Join us at Scout Motors and be part of shaping the future of transportation. If you're ready to drive change and make history, apply now! About the team The AI Team is responsible for building the organization’s intelligent technology capabilities by designing, developing, and scaling AI-powered products and platforms across the enterprise. The team combines expertise in machine learning, generative AI, data engineering, and platform infrastructure to deliver innovative solutions that improve business outcomes and accelerate digital transformation. The team focuses on: Developing machine learning and generative AI solutions that solve high-impact business problems. Building scalable AI infrastructure, including model training, deployment, and inference platforms. Creating reusable AI platforms, APIs, and shared services for enterprise-wide adoption. Partnering with product, engineering, data, and business teams to identify and prioritize AI use cases. Evaluating emerging AI technologies and rapidly prototyping new capabilities. Establishing best practices in MLOps, LLMOps, governance, security, and responsible AI. The AI Team operates at the intersection of innovation and engineering excellence, transforming advanced AI technologies into production-grade enterprise solutions. 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: Lead the design, implementation, and evolution of scalable AI platforms Collaborate cross-functionally with product managers, architects, developers, data engineers, and business leaders to deliver robust, production-grade AI solutions. Design end-to-end AI data architectures, including feature stores, vector databases, knowledge repositories, and model-ready data pipelines. Lead the design, training, fine-tuning, deployment, and lifecycle management of machine learning and generative AI models. Design and oversee ETL/ELT pipelines in Python to support model training, inference, retrieval-augmented generation (RAG), and intelligent automation workflows. Lead development of AI-powered dashboards and observability platforms to monitor model performance, trends, forecasts, drift, and operational health. Design and implement resilient AI infrastructure components, ensuring high availability, scalability, reliability, and performance for training and inference workloads. Establish governance standards to ensure AI systems adhere to enterprise data quality, security, privacy, and compliance policies. Build and govern MLOps / LLMOps frameworks including model registries, CI/CD pipelines, prompt versioning, automated retraining, and inference monitoring. Implement proactive monitoring and alerting solutions for AI systems, including latency, hallucination risk, drift detection, and infrastructure health. Partner with cybersecurity and compliance teams to ensure AI platforms meet enterprise security, regulatory, and responsible AI standards. Evaluate emerging AI tools, frameworks, and infrastructure platforms, and prototype new capabilities to accelerate enterprise AI innovation. Mentor and lead AI engineers and platform teams, establishing engineering best practices for scalable AI solution delivery. Location & Travel Expectations : This role may be based out of the Scout Motors corporate headquarters in Charlotte, NC or in Fremont, California. This role requires 4 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 or master’s degree in computer science, Artificial Intelligence, Information Technology, Engineering, or a related field, or equivalent practical experience. 8+ years of hands-on experience in AI/ML engineering, machine learning platforms, data engineering, or AI infrastructure, with experience in enterprise-scale environments such as manufacturing, automotive, or similarly complex industries. 3+ years of experience leading or mentoring AI engineering, ML engineering, or platform engineering teams. Strong experience designing and deploying end-to-end AI solutions, including machine learning, generative AI, and LLM-based applications. Proficiency in Python, SQL, and modern AI/ML frameworks such as PyTorch, TensorFlow, Scikit-learn, LangChain, or equivalent platforms. Experience building scalable AI data pipelines supporting model training, inference, RAG architecture, and intelligent automation workflows. Hands-on expertise with cloud AI and data services such as AWS SageMaker, Glue, Kinesis, Firehose, Azure ML, Vertex AI, or comparable platforms. Strong knowledge of structured, unstructured, streaming, and time-series data architecture, including experience with vector databases and embedding stores. Experience with enterprise data platforms and lakehouse architecture such as Databricks, Delta Lake, or equivalent modern data ecosystems. Solid understanding of cloud-native storage and database platforms including RDS, DynamoDB, MongoDB, Cassandra, DocumentDB, Influx DB, and AI-ready vector data systems. Experience architecting scalable AI infrastructure using Kubernetes, Docker, GPU-enabled environments, distributed compute clusters, and Infrastructure as Code tools such as Terraform. Proven ability to design, train, fine-tune, deploy, and monitor scalable machine learning and generative AI models in production environments. Experience implementing MLOps / LLMOps practices including CI/CD pipelines, model registries, prompt versioning, automated retraining, and observability frameworks. Excellent problem-solving and troubleshooting skills, with a proactive ownership mindset toward resolving complex technical challenges. Strong communication, collaboration, and leadership skills, with the ability to influence cross-functional teams and guide architectural decisions while fostering a culture of engineering excellence. 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 = $180,000.00 - $220,000.00 IInitial California, Washington and New York base salary range: $209,000 - $253,000 Internal leveling code: IC7 Notice to applicants: To be considered for career opportunities at Scout Motors, applicants must be 18 years of age or older. Residing in San Francisco : Pursuant to the San Francisco Fair Chance Ordinance, Scout Motors will consider for employment qualified applicants with arrest and conviction records. Residing in Los Angeles : Scout Motors will consider for employment qualified applicants with criminal histories in a manner consistent with the Los Angeles Fair Chance Initiative for Hiring Ordinance. Residing in New York City : This role is not eligible for remote work in New York City. Equal Opportunity Scout Motors is committed to employing a diverse workforce and is proud to be an Equal Opportunity Employer . Qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, gender expression, veteran status, disability, pregnancy, or any other characteristics protected by law. Scout Motors is committed to compliance with all ap p licable fair employment p ractice laws . If you require reasonable accommodation to complete a job application, pre-employment testing, or a job interview or to otherwise participate in the hiring process, please contact ScoutAccommodations@scoutmotors.com.

Requirements

Must-haves

But Scout is more than just a brand, it’s a legacy steeped in a culture of exploration, caretaking, and hard work.
Join us at Scout Motors and be part of shaping the future of transportation. If you're ready to drive change and make history, apply now! About the team
Developing machine learning and generative AI solutions that solve high-impact business problems.
Building scalable AI infrastructure, including model training, deployment, and inference platforms.
Creating reusable AI platforms, APIs, and shared services for enterprise-wide adoption.
Partnering with product, engineering, data, and business teams to identify and prioritize AI use cases.
Evaluating emerging AI technologies and rapidly prototyping new capabilities.
Establishing best practices in MLOps, LLMOps, governance, security, and responsible AI.
The AI Team operates at the intersection of innovation and engineering excellence, transforming advanced AI technologies into production-grade enterprise solutions.
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:
Lead the design, implementation, and evolution of scalable AI platforms
Collaborate cross-functionally with product managers, architects, developers, data engineers, and business leaders to deliver robust, production-grade AI solutions.
Design end-to-end AI data architectures, including feature stores, vector databases, knowledge repositories, and model-ready data pipelines.
Lead the design, training, fine-tuning, deployment, and lifecycle management of machine learning and generative AI models.
Design and oversee ETL/ELT pipelines in Python to support model training, inference, retrieval-augmented generation (RAG), and intelligent automation workflows.
Lead development of AI-powered dashboards and observability platforms to monitor model performance, trends, forecasts, drift, and operational health.
Design and implement resilient AI infrastructure components, ensuring high availability, scalability, reliability, and performance for training and inference workloads.
Establish governance standards to ensure AI systems adhere to enterprise data quality, security, privacy, and compliance policies.
Build and govern MLOps / LLMOps frameworks including model registries, CI/CD pipelines, prompt versioning, automated retraining, and inference monitoring.
Implement proactive monitoring and alerting solutions for AI systems, including latency, hallucination risk, drift detection, and infrastructure health.
Partner with cybersecurity and compliance teams to ensure AI platforms meet enterprise security, regulatory, and responsible AI standards.
Evaluate emerging AI tools, frameworks, and infrastructure platforms, and prototype new capabilities to accelerate enterprise AI innovation.
Mentor and lead AI engineers and platform teams, establishing engineering best practices for scalable AI solution delivery.

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goaimachine learningpythonci/cdmlllmsqlawsazurekubernetesdocker

Platform: greenhouse
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Benefits

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Dental

Vision

401(K)

Pto

Paid Time Off

Parental Leave