{"id":4300904,"url":"https://alion.io/job/indigo-beam-deep-learning-data-scientist","title":"Deep Learning Data Scientist","company":{"id":689717,"name":"Indigo Beam","domain":"indigobeam.com","url":"https://alion.io/company/indigobeam","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Zoho Recruit","truth_index":{"grade":"A","score":95,"open_postings":3,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":62,"computed_at":"2026-11-12T10:38:37Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"contractor","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Houston, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"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":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Bash","optional":false},{"name":"Git","optional":false},{"name":"HPC","optional":false},{"name":"LLM","optional":false},{"name":"Multimodal AI","optional":false},{"name":"PyTorch","optional":false},{"name":"Transformers","optional":false},{"name":"Unix","optional":false}],"status":"live","first_seen_at":"2026-11-14T03:08:51Z","employer_posted_date":"2026-11-14","last_verified_at":"2026-11-14T03:08:51Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Deep Learning Data Scientist Location: Houston, TX (on-site, 5 days per week) Type: ContractRole Summary We are looking for a Deep Learning Data Scientist to research and develop deep learning technologies for business problems across energy datasets for a global energy client. You will work with business stakeholders and engineers to prototype, implement, evaluate and evolve AI products.\nKey\nResponsibilities Translate business problems into technical AI solutions and execute implementation. Design, implement and evaluate deep learning solutions across diverse datasets such as upstream and renewables. Prototype and implement domain-specific AI solutions and work with engineers across the product lifecycle. Engage stakeholders and contribute to scientific and industry knowledge.\nRequirements Deep learning expertise, including CNNs and Transformers. Advanced analytics algorithms and model development. Multimodal LLM architectures and algorithms. Familiarity with agentic workflows / AI Foundry. PyTorch, Git and distributed model training on HPC clusters. Azure/AWS cloud architectures and Unix/Bash. Master's or PhD in a STEM field plus relevant deep learning experience. Energy industry experience preferred. 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