{"id":1194041,"url":"https://alion.io/job/slate-senior-aiml-engineer","title":"Senior AI/ML Engineer","company":{"id":1772423,"name":"Slate","domain":"slate.auto","url":"https://alion.io/company/slate-auto","size_band":null,"is_staffing_agency":false,"is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":115000,"max_usd":252000,"period":"year","method":"global_role_seniority_cell","sample_n":1271},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Computer Vision","optional":false},{"name":"Embeddings","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GCP","optional":false},{"name":"Gemini","optional":false},{"name":"Hugging Face","optional":false},{"name":"JAX","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"OpenAI","optional":false},{"name":"Physical AI","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Time Series Forecasting","optional":false}],"status":"live","first_seen_at":"2026-09-24T18:10:47Z","employer_posted_date":null,"last_verified_at":"2026-09-24T18:10:47Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"This a Full Remote job, the offer is available from: Nevada (USA)\nABOUT SLATE\nAt Slate, we’re building safe, reliable vehicles that people can afford, personalize and love-and doing it here in the USA as part of our commitment to reindustrialization. The spirit of DIY and customization runs throughout every element of a Slate, because people should have control over how their trucks look, feel, and represent them.\nPosition Overview\nSlate Automotive is building an AI-native vehicle platform from the ground up. This role is for an engineer ready to work on real AI/ML problems in production: GenAI features, data pipelines, and AI applied to manufacturing and supply chain operations.\nWe are open to candidates early in their careers if they have the right foundation. A PhD in a relevant field is a strong signal; engineers without one should bring equivalent depth through demonstrated project work, research, or professional experience. What matters is that you can build things, learn fast, and are genuinely interested in applying AI to physical and operational systems.\nThe role reports to the Distinguished Engineer of Generative AI.\nWhat You Will Do\nBuild and ship AI/ML features. Work across the model lifecycle: data preparation, training or fine-tuning, evaluation, deployment, and monitoring. Own features end-to-end and iterate based on real production feedback.\nContribute to GenAI systems. Build RAG pipelines, work with LLM APIs and open-source models, design prompts for reliability, and contribute to agentic workflows. You will work on the full GenAI stack hands-on.\nBuild data and evaluation infrastructure. Write data pipelines, labeling workflows, and evaluation frameworks. Reliable evals are a first-class deliverable on this team.\nWork on manufacturing, supply chain, and physical operations problems. Slate operates a factory with a real supply chain. You will be exposed to AI problems in both areas: computer vision for quality inspection, predictive maintenance, and sensor data on the physical side; demand forecasting, inventory planning, supplier risk, and logistics on the supply chain side. We are particularly interested in candidates who are drawn to this kind of work.\nCollaborate across the organization. Work with Vehicle Engineering, Manufacturing, and Operations to understand requirements and translate them into AI systems that produce measurable output.\nWho You Are\nTechnically grounded in ML. You understand how models are trained and evaluated, not just how to call an API. You have built something end-to-end - a project, a thesis, a production system - that demonstrates that.\nInterested in physical and operational AI. Candidates drawn to the intersection of AI and the physical world - manufacturing systems, robotics, logistics, industrial data - will find the most to work on and will ramp fastest. Not a requirement, but a clear differentiator.\nA fast learner. The GenAI landscape moves quickly and so does Slate. You pick up new tools and domains without needing everything handed to you.\nHands-on. You write code, run experiments, and ship things. Research interest without engineering follow-through is not a fit for this role.\nCollaborative and clear. You work well across disciplines and can explain technical decisions to non-technical stakeholders. Be willing to directly interreact with stakeholders to build product without the need for a product manager.\nTechnical Requirements\nA PhD in a relevant field is a strong foundation for someone early in their career and is treated as such. Candidates without a PhD should bring 3+ years of professional or research experience working directly on ML systems. In either case, the bar is the same: you need to demonstrate you can build.\nMachine Learning and Generative AI\nFoundational understanding of ML: model training, loss functions, evaluation metrics, overfitting, and regularization.\nPractical experience with: supervised learning, NLP, computer vision, and time-series modeling.\nFamiliarity with LLM APIs (OpenAI, Anthropic, Gemini, or similar) and how to build reliably on top of them.\nBasic exposure to RAG, embeddings, or retrieval systems - including in a project or research context.\nAbility to evaluate model quality rigorously, not just report accuracy on a held-out set.\nSoftware Engineering\nPython proficiency: comfortable with the ML stack (PyTorch or JAX, Hugging Face, pandas, scikit-learn).\nAbility to write production-quality code, not just notebook code.\nFamiliarity with cloud platforms (AWS, GCP, or Azure) at a working level.\nVersion control, experiment tracking, and basic MLOps practices.\nManufacturing, Physical AI, and Supply Chain (Valued)\nPreferred. Candidates with background or genuine interest in any of the following will stand out.\nAcademic or professional background in Mechanical Engineering, Electrical Engineering, Robotics, Industrial Engineering, or a related physical discipline.\nExposure to computer vision, sensor data, or real-time systems - including coursework or personal projects.\nFamiliarity with supply chain, logistics, or operations research problems.\nExperience with simulation environments or physical hardware in a research or lab setting.\nAcademic Grounding\nBS required. MS or PhD in Computer Science, Machine Learning, Robotics, Electrical Engineering, Mechanical Engineering, Industrial Engineering, or a related field preferred. A PhD is treated as a strong signal for early-career candidates. Candidates without advanced degrees should bring equivalent depth through their project or professional work.\nSALARY RANGE\nThe compensation for this position is the range Slate reasonably and in good faith expects to pay for the position taking into account the wide variety of factors that are considered in making compensation decisions, including job-related knowledge; skillset; experience, education and training; certifications; work location; and other relevant business and organizational factors.\nBase Pay Range (Annual)\n141,807.00 - 177,259.00 - 212,710.00 USD Annual\nAdditional Compensation and Benefits: Slate offers a wide range of competitive benefits, including medical, dental, vision, life insurance, disability insurance, vacation, and 401k. The successful candidate may also be eligible to participate in the equity program and/or a discretionary annual incentive program, subject to the rules governing such programs.\nWHY JOIN TEAM SLATE?\nAt Slate, we’re fueled by grit, determination, and attention to detail. The start-up spirit of ingenuity and resourcefulness move our business forward. Team Slate fosters a culture of excellence, innovation, and mutual respect, and is motivated by shared principles.\nSafety First\n\nDelight Customers\n\nOne Team\n\nRelentless Improvement\n\nFast, Frugal, and Scrappy\n\nRespectful Collaboration\n\nPositive Legacy\n\nWE WANT TO WORK WITH PEOPLE THAT REFLECT THE COMMUNITIES IN WHICH WE OPERATE.\nSlate is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, marital status, parental status, cultural background, organizational level, work styles, tenure and life experiences. Or for any other reason.\nSlate is committed to providing reasonable accommodation for qualified individuals with disabilities in our job application procedures. If you need assistance or an accommodation due to a disability, you may contact us at\n.","description_format":"text","description_chars":7569,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["401k plan","Equity","Life insurance"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-09-24T18:10:47Z"}],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":25,"reasons":["seen:0","win:early","comp:brand"],"computed_at":"2026-09-24T23:07:53Z"},"pay":null,"html_url":"https://alion.io/job/slate-senior-aiml-engineer","json_url":"https://alion.io/job/slate-senior-aiml-engineer.json","meta":{"generated_at":"2026-09-24T23:07:53Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":1327,"day_limit":5000,"remaining_today":3673,"minute_limit":60,"resets_at":"2026-09-25T00:00:00Z"}}}