{"id":2559771,"url":"https://alion.io/job/mutt-data-machine-learning-ai-engineer-lead-databricks-eng","title":"Machine Learning / AI Engineer Lead - Databricks - Eng","company":{"id":19043,"name":"Mutt Data","domain":"muttdata.ai","url":"https://alion.io/company/mutt-data","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":79,"open_postings":12,"ghost_share":0,"stale_share":0.833,"repost_share":0,"time_to_fill_p50_days":33,"computed_at":"2026-10-15T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Argentina"],"countries":["AR"],"hiring_countries":["AR"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":60000,"max_usd":144000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1119},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AIOps","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Spark","optional":false}],"status":"live","first_seen_at":"2026-10-14T19:48:43Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-15T04:07:32Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Join Our Data Products and Machine Learning Development Remote Startup!\nMutt Data is a dynamic startup committed to crafting innovative systems using cutting-edge Big Data and Machine Learning technologies.\nWe’re looking for a Machine Learning / AI Engineer Lead to help take our expertise to the next level. If you consider yourself a data nerd like us, we’d love to connect!\nWhat We Do\nLeveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.\nDeveloping scalable data infrastructures, we enhance high-level decision-making, tailored to each client.\nOffering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems.\nUsing Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster.\nBuilding deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.\nDeveloping recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.\nOur Partnerships\nAmazon Web Services\nAstronomer\nDatabricks\nOur Values\n We are Data Nerds\n We are Open Team Players\n We Take Ownership\n We Have a Positive Mindset\nCurious about what we’re up to? Check out our case studies and dive into our blog post to learn more about our culture and the exciting projects we’re working on!\nResponsibilities\nServe as a primary technical consultant, leading and executing end-to-end AI/ML project implementationsdirectly with clients, translating complex business problems into robust technical solutions.\n\nExhibit excellent communication, presentation, and stakeholder management skills to clearlyarticulate technical findings, proposals, and project status to both technical and non-technical audiences.\n\n Design, build, and maintain production-grade AI and ML pipelines, focusing on continuous integration,continuous delivery (CI/CD), and advanced MLOps/AIOps practices to ensure reliability and scalability of\nmodels.\n\nImplement and optimize cutting-edge Generative and Agentic AI applications, demonstrating hands-onexperience with technologies like multi-agent orchestration, agent evaluation, and Retrieval Augmented\nGeneration(RAG) Systems in a production setting.\n\nArchitect end-to-end AI/ML systems, designing both traditional Machine Learning- and Generative AI-basedsolutions based on customer requirements\n\nManage underlying solution infrastructure necessary for production deployment, demonstrating proficiencyin technologies such as Docker, pipeline orchestrators, and lakehouse database systems like Databricks.\n\nLeverage expertise in distributed computing frameworks, specifically in scalable machine learning and high-performance data processing (e.g., using technologies like Apache Spark).\n\nContribute to the strategic growth of the AI FDE Practice, including participation in technical assignmentsand knowledge transfer activities.\n\nEnsure all client engagements and training activities are properly documented and reported via designatedpartner platforms.\n\nRequired Skills\n4+ years of hands-on professional experience developing, deploying, and managing Generative/Agentic AIor Machine Learning systems, with a mandatory requirement for productionizing and maintaining models in\na live environment.\n\n3+ years of experience in a customer-facing consulting or solutions architect role, focused on technicalimplementation and delivery.\n\nExcellent verbal and written communication skills for effective client and internal team interaction.\nExpertise in MLOps lifecycle management, including model versioning, testing, monitoring, and automateddeployment best practices.\n\nDemonstrable experience with infrastructure management, encompassing containerization (Docker) anddata pipeline orchestration.\n\nExpertise in Python for data-intensive and scalable AI/ML applications.\nDemonstrated commitment to continuous learning in emerging AI/ML fields.\nPerks\nRemote-first culture - work from anywhere! 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