{"id":3685667,"url":"https://alion.io/job/weekday-ai-engineer-8","title":"AI 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":"2026-11-07T05:47:08Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Bengaluru, India"],"countries":["IN"],"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":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"BERT","optional":false},{"name":"CI/CD","optional":false},{"name":"Diffusion Models","optional":false},{"name":"Docker","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GCP","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Rest API","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Stable Diffusion","optional":false},{"name":"TensorFlow","optional":false}],"status":"closed","first_seen_at":"2026-11-03T14:52:16Z","employer_posted_date":"2026-11-03","last_verified_at":"2026-11-05T16:44:12Z","board_verified":false,"closed_at":"2026-11-05T16:44:12Z","days_open":2,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":2},"description":"'\n: - ( - )\nExperience: 5+ yrs\nLocation: Bengaluru, Karnataka, India\nAs a AI Engineer, you will spearhead the development and deployment of cutting-edge artificial intelligence solutions that drive business value for complex, data-rich environments. You will design, implement, and optimise machine learning pipelines, leveraging advanced generative AI techniques and ensuring scalability across cloud platforms. Your work will involve close collaboration with data scientists, product managers, and domain experts to translate business challenges into robust AI models that are both performant and auditable. With a strong foundation in Python and deep expertise in MCP frameworks, you will continuously iterate on model performance and integrate new AI capabilities into existing systems, while maintaining high standards of code quality and documentation.\nRequirements\nDesign and develop end-to-end AI solutions using Python, TensorFlow/PyTorch, and MCP tools.\nBuild and maintain scalable machine learning pipelines that support real-time inference and batch processing.\nIntegrate generative AI models (e.g., GPT, Stable Diffusion) into product workflows to enhance user experience and content creation.\nConduct rigorous model validation, testing, and performance evaluation to ensure reliability and compliance with industry standards.\nOptimize models for latency, throughput, and resource utilization across on-premise and cloud infrastructures.\nWork closely with data engineering teams to curate high-quality datasets and implement data ingestion workflows.\nCollaborate with software engineers to embed AI services into microservices architectures and RESTful APIs.\nMonitor deployed models for drift, accuracy, and ethical considerations, implementing retraining pipelines as needed.\nLead code reviews and mentor junior engineers on best practices in AI development and deployment.\nStay abreast of the latest research in generative AI and MCP, translating cutting-edge findings into practical solutions.\n5+ years of professional experience in AI/Machine Learning engineering roles.\nProven expertise in Python, including advanced libraries such as NumPy, Pandas, Scikit-Learn, and deep learning frameworks.\nHands-on experience with MCP (Model Compression and Pruning) techniques for deploying models on edge and low-latency environments.\nStrong background in designing, training, and fine-tuning generative AI models like GPT, BERT, and Diffusion models.\nDemonstrated ability to deploy AI solutions at scale using Kubernetes, Docker, and cloud platforms (AWS, GCP, Azure).\nExcellent problem-solving skills with a track record of delivering robust, production-ready AI systems.\nAbility to translate complex technical concepts into clear, actionable insights for cross-functional teams.\nStrong communication skills, comfortable presenting findings to both technical and non-technical stakeholders.\nExperience with CI/CD pipelines and automated testing frameworks for AI models.\nA passion for continuous learning, staying updated on emerging AI research and industry best practices.","description_format":"text","description_chars":3084,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Continuous 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