{"id":1108046,"url":"https://alion.io/job/weekday-staff-machine-learning-engineer","title":"Staff Machine Learning Engineer","company":{"id":7097,"name":"Weekday","domain":"weekday.works","url":"https://alion.io/company/weekday","size_band":"51-200","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":81,"open_postings":100,"ghost_share":0,"stale_share":0.98,"repost_share":0,"time_to_fill_p50_days":6,"computed_at":"2026-11-09T06:03:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":40000,"max_usd":92000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":13},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"Feature Store","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Gemini","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"Llama","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Mistral","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"NLP","optional":false},{"name":"OpenAI","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"RAG","optional":false},{"name":"Recommender Systems","optional":false},{"name":"AWS","optional":true},{"name":"Docker","optional":true},{"name":"GCP","optional":true},{"name":"Kubernetes","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"Reinforcement Learning","optional":true},{"name":"Scikit-learn","optional":true},{"name":"Spark","optional":true},{"name":"SQL","optional":true},{"name":"TensorFlow","optional":true}],"status":"live","first_seen_at":"2026-09-22T07:46:13Z","employer_posted_date":"2026-09-22","last_verified_at":"2026-11-10T02:42:15Z","board_verified":true,"closed_at":null,"days_open":48,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":48},"description":"This role is for one of Weekday’s clients\nMin Experience: 10+ years\nLocation: Bengaluru\nJobType: full-time\nWe are seeking a highly experienced Staff Machine Learning Engineer to lead the architecture, development, and scaling of enterprise-grade Machine Learning and Generative AI platforms.\nAs a senior technical leader, you will drive AI strategy, establish engineering best practices, mentor ML engineers, and collaborate cross-functionally with Product, Engineering, Data, and Business stakeholders to deliver measurable business outcomes. You will play a critical role in shaping our AI roadmap and building intelligent products that impact thousands of businesses globally.\nThe ideal candidate will have 8+ years of experience building and deploying large-scale ML systems, deep expertise across the full ML lifecycle, and hands-on experience delivering production-grade Generative AI solutions at scale.\nRequirements\nKey Responsibilities\nTechnical Leadership\nDefine and drive the technical vision for Machine Learning and Generative AI initiatives.\nLead architecture reviews and establish best practices for scalable AI systems.\nMentor and guide ML engineers and data scientists across teams.\nInfluence product strategy through AI-driven innovation and technical thought leadership.\nPartner with Engineering leadership to build scalable, reliable, and secure AI platforms.\nMachine Learning & Data Science\nDesign, develop, and deploy large-scale ML solutions in production environments.\nBuild advanced predictive models, recommendation systems, forecasting solutions, NLP applications, and deep learning systems.\nDrive the complete machine learning lifecycle:\nProblem definition\nData acquisition and exploration\nFeature engineering\nModel development\nModel evaluation and validation\nProduction deployment\nMonitoring, governance, and continuous improvement\nDevelop frameworks and reusable components to accelerate ML development across teams.\nEstablish model governance, explainability, fairness, and compliance standards.\nGenerative AI & LLM Applications\nArchitect and deliver enterprise-scale GenAI solutions leveraging:\nOpenAI\nAzure OpenAI\nAnthropic Claude\nLlama\nMistral\nGemini\nDesign and implement:\nAdvanced RAG architectures\nAgentic AI systems\nMulti-agent workflows\nAI orchestration frameworks\nPrompt engineering and evaluation frameworks\nFine-tuning and model adaptation pipelines\nKnowledge graph-assisted AI systems\nAI observability and evaluation frameworks\nLead experimentation and adoption of emerging AI technologies to create competitive advantage.\nPlatform Engineering & MLOps\nArchitect scalable ML platforms and infrastructure.\nBuild and optimize end-to-end ML pipelines.\nDrive MLOps best practices including:\nCI/CD for ML\nModel serving\nFeature stores\nExperiment tracking\nMonitoring and observability\nAutomated retraining pipelines\nModel governance and security\nOptimize system performance, scalability, reliability, and cost efficiency.\nCross-Functional Collaboration\nPartner with Product Managers, Engineering leaders, and Business stakeholders to identify high-impact AI opportunities.\nTranslate business problems into scalable AI solutions.\nDefine success metrics and measure business impact.\nDrive AI adoption and technical excellence across the organization.\nPreferred Qualifications\nExperience\n10+ years of experience in Machine Learning, Data Science, and AI Engineering.\nProven track record of delivering production-grade AI/ML products at scale.\nExperience leading complex technical initiatives and influencing engineering direction.\nExperience mentoring engineers and driving technical excellence across teams.\nTechnical Skills\nStrong expertise in Python, SQL, and distributed computing frameworks such as Spark.\nDeep knowledge of machine learning and deep learning frameworks:\nPyTorch\nTensorFlow\nScikit-learn\nStrong expertise in:\nLarge Language Models (LLMs)\nRetrieval-Augmented Generation (RAG)\nAgentic AI Systems\nReinforcement Learning concepts\nAI Evaluation Frameworks\nHands-on experience with:\nDocker\nKubernetes\nAWS, Azure, or GCP\nVector Databases\nAPI and Microservices Architecture\nExpertise in:\nMLOps\nModel Deployment\nFeature Stores\nExperiment Tracking\nObservability and Monitoring\nLeadership Attributes\nStrong architectural and systems-thinking mindset.\nAbility to influence without authority and drive cross-functional alignment.\nExceptional communication and stakeholder management skills.\nPassion 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