Slm Solutions Jobs (NOW HIRING)

Rivian is on a mission to keep the world adventurous forever. This goes for the emissions-free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract. 

As a company, we constantly challenge what’s possible, never simply accepting what has always been done. We reframe old problems, seek new solutions and operate comfortably in areas that are unknown. Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations. 

Rivian's AI team sits within the Analytics function of the Customer organization—the team that spans Marketing, Sales, and Market Intelligence—and is building the next generation of intelligent, autonomous systems that connect these functions into a single, reasoning ecosystem. As a Staff/Lead Data Scientist focused on Agentic Solutions, you will design and operationalize the cognitive architecture that powers Rivian's AI agents—building the reasoning loops, retrieval systems, and evaluation frameworks that allow agents to act on live business data with accuracy and reliability. This is a deeply technical, high-impact role at the frontier of applied AI, working closely with Context Engineering, Data Platform, and the broader Customer org Analytics team to bring agentic intelligence to production.

Agent Orchestration & Cognitive Architecture

• Agentic Reasoning Loops: Design and program multi-step reasoning frameworks using orchestration frameworks like LangChain, LlamaIndex, or Haystack.
• Context Engineering & Advanced RAG: Architect advanced retrieval structures, experimenting with embedding models, dynamic chunking strategies, and token management to ensure agents receive high-fidelity business context.
• Proactive System Reasoning: Build the internal logic and evaluation criteria for 'Watchdog' agents, enabling them to analyze live operational data streams, infer anomalies, and formulate proactive insights.

Applied Data Science & Model Optimization

• Small Language Model (SLM) Strategy: Evaluate, select, and adapt small language models (e.g., Phi, Mistral, Gemma) for domain-specific agentic tasks where precision, latency, and cost efficiency outweigh raw model scale. Design the decision framework for when to use an SLM vs. a frontier model based on task complexity, context requirements, and inference cost.
• Token Economics & Efficient Agent Design: Architect agents and orchestration frameworks around token efficiency as a first-class design constraint—developing strategies for context compression, prompt caching, dynamic context windowing, and call minimization to ensure every inference call is purposeful and cost-effective at scale.
• Domain-Specific Model Adaptation: Execute parameter-efficient fine-tuning (e.g., LoRA/QLoRA) and model distillation on open-source models to embed Rivian's fulfillment jargon, vehicle logistics vocabulary, and internal business rules—prioritizing targeted SLM adaptation over large-scale LLM retraining where feasible.
• Rigorous Evaluation Frameworks: Establish statistical, model-driven, and human-in-the-loop testing benchmarks to empirically validate agent reasoning, track accuracy drift, and minimize hallucinations.
• Behavioral Prompt Engineering: Continuously iterate on complex system prompting, structured output formats (e.g., enforcing strict JSON/tool schemas), and cognitive guardrails to keep agent behavior deterministic and aligned.

• Education: Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field; Master's or PhD preferred.
• Experience: 5+ years in Machine Learning, Applied Data Science, or AI Engineering, with a proven track record of designing cognitive frameworks, RAG systems, or agentic workflows for business applications.
• Orchestration Mastery: Expert-level capability with modern AI orchestration frameworks (LangChain, LlamaIndex, Haystack) and a deep understanding of LLM APIs, prompt engineering methodologies, and agent memory state management.
• Small Language Model Expertise: Hands-on experience working with SLMs (e.g., Phi, Mistral, Gemma) for domain-specific deployment; ability to reason about the trade-offs between model size, latency, cost, and task accuracy. Experience with parameter-efficient fine-tuning (LoRA/QLoRA) and model distillation.
• Token Management & Cost-Efficient Architecture: Deep understanding of token economics; experience designing agent frameworks with context compression, prompt caching, dynamic windowing, and call-minimization strategies to build systems that are both intelligent and economically viable at scale.
• Data & Language Stack: Expert-level Python and highly proficient SQL. Comfortable inside Databricks (Spark, Delta Lake) navigating structured relational schemas, metadata, and vector indices to extract and optimize model context.
• Analytical Literacy: Strong statistical foundation with familiarity analyzing user behavioral data or event-streams (e.g., Snowplow) to help agents deduce funnel health and operational anomalies.
• Environment: Proven ability to operate in a fast-paced, high-ambiguity environment—such as a new product launch or startup-stage AI build—with intellectual curiosity, rigorous attention to detail, and a bias for shipping.
• Ability to stand, sit, or walk for 8-10 hours per day.
• Required to communicate using phone and/or e-mail.
• Ability to view, read, and interpret documents.
• Ability to perform all duties in an office environment that may contain ambient noise and temperature fluctuations. 

The salary range for this role is $171,100 to $213,900 for Irvine, CA and El Segundo, CA based applicants. This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee’s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, geographic location, shift, and organizational needs.

The successful candidate may be eligible for annual performance bonus and equity awards.

We offer a comprehensive package of benefits for full-time and part-time employees, their spouse or domestic partner, and children up to age 26, including but not limited to paid vacation, paid sick leave, and a competitive portfolio of insurance benefits including life, medical, dental, vision, short-term disability insurance, and long-term disability insurance to eligible employees. You may also have the opportunity to participate in Rivian’s 401(k) Plan and Employee Stock Purchase Plan if you meet certain eligibility requirements. Full-time employee coverage is effective on their first day of employment. Part-time employee coverage is effective the first of the month following 90 days of employment. More information about benefits is available at rivianbenefits.com.

You can apply for this role through careers.rivian.com (or through internal-careers-rivian.icims.com if you are a current employee). This job is not expected to be closed any sooner than July 31, 2026.

Rivian is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, sex, sexual orientation, gender, gender expression, gender identity, genetic information or characteristics, physical or mental disability, marital/domestic partner status, age, military/veteran status, medical condition, or any other characteristic protected by law.

Rivian is committed to ensuring that our hiring process is accessible for persons with disabilities. If you have a disability or limitation, such as those covered by the Americans with Disabilities Act, that requires accommodations to assist you in the search and application process, please email us at candidateaccommodations@rivian.com.

Rivian may collect, use and disclose your personal information or personal data (within the meaning of the applicable data protection laws) when you apply for employment and/or participate in our recruitment processes (“Candidate Personal Data”). This data includes contact, demographic, communications, educational, professional, employment, social media/website, network/device, recruiting system usage/interaction, security and preference information. Rivian may use your Candidate Personal Data for the purposes of (i) tracking interactions with our recruiting system; (ii) carrying out, analyzing and improving our application and recruitment process, including assessing you and your application and conducting employment, background and reference checks; (iii) establishing an employment relationship or entering into an employment contract with you; (iv) complying with our legal, regulatory and corporate governance obligations; (v) recordkeeping; (vi) ensuring network and information security and preventing fraud; and (vii) as otherwise required or permitted by applicable law. 

Rivian may share your Candidate Personal Data with (i) internal personnel who have a need to know such information in order to perform their duties, including individuals on our People Team, Finance, Legal, and the team(s) with the position(s) for which you are applying; (ii) Rivian affiliates; and (iii) Rivian’s service providers, including providers of background checks, staffing services, and cloud services. 

Rivian may transfer or store internationally your Candidate Personal Data, including to or in the United States, Canada, the United Kingdom, and the European Union and in the cloud, and this data may be subject to the laws and accessible to the courts, law enforcement and national security authorities of such jurisdictions.  

How We Use AI in Our Hiring Process: To ensure transparency, we want candidates to know that Rivian uses iCIMS Talent Cloud Artificial Intelligence (TCAI) and AI-enabled tools to assist with screening, reviewing, organizing and highlighting profiles and applications that match the key requirements for each role.

Participation in AI profile matching is entirely voluntary. If you prefer that your profile not be used in this process, you can opt out at any time. Opting out means your profile will be excluded from automated matching and will not be surfaced for additional roles through this system. Your current application remains active and will not be affected in any way.

Please note that we are currently not accepting applications from third party application services.

• Education: Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field; Master's or PhD preferred.
• Experience: 5+ years in Machine Learning, Applied Data Science, or AI Engineering, with a proven track record of designing cognitive frameworks, RAG systems, or agentic workflows for business applications.
• Orchestration Mastery: Expert-level capability with modern AI orchestration frameworks (LangChain, LlamaIndex, Haystack) and a deep understanding of LLM APIs, prompt engineering methodologies, and agent memory state management.
• Small Language Model Expertise: Hands-on experience working with SLMs (e.g., Phi, Mistral, Gemma) for domain-specific deployment; ability to reason about the trade-offs between model size, latency, cost, and task accuracy. Experience with parameter-efficient fine-tuning (LoRA/QLoRA) and model distillation.
• Token Management & Cost-Efficient Architecture: Deep understanding of token economics; experience designing agent frameworks with context compression, prompt caching, dynamic windowing, and call-minimization strategies to build systems that are both intelligent and economically viable at scale.
• Data & Language Stack: Expert-level Python and highly proficient SQL. Comfortable inside Databricks (Spark, Delta Lake) navigating structured relational schemas, metadata, and vector indices to extract and optimize model context.
• Analytical Literacy: Strong statistical foundation with familiarity analyzing user behavioral data or event-streams (e.g., Snowplow) to help agents deduce funnel health and operational anomalies.
• Environment: Proven ability to operate in a fast-paced, high-ambiguity environment—such as a new product launch or startup-stage AI build—with intellectual curiosity, rigorous attention to detail, and a bias for shipping.
• Ability to stand, sit, or walk for 8-10 hours per day.
• Required to communicate using phone and/or e-mail.
• Ability to view, read, and interpret documents.
• Ability to perform all duties in an office environment that may contain ambient noise and temperature fluctuations.