{"id":2458135,"url":"https://alion.io/job/blackrock-artificial-intelligence-engineer-portfolio-management-group-associate","title":"Artificial Intelligence Engineer, Portfolio Management Group, Associate","company":{"id":5262,"name":"BlackRock","domain":"blackrock.com","url":"https://alion.io/company/blackrock","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":92,"open_postings":3,"ghost_share":0,"stale_share":0.333,"repost_share":0,"time_to_fill_p50_days":24,"computed_at":"2026-10-22T06:10:10Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mumbai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":17500,"max_usd":47000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":31},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Embeddings","optional":false},{"name":"FAISS","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"GitHub","optional":false},{"name":"Hugging Face","optional":false},{"name":"Interpretability","optional":false},{"name":"LangChain","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"Pandas","optional":false},{"name":"Pinecone","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Snowflake","optional":false},{"name":"TensorFlow","optional":false},{"name":"Time Series","optional":false}],"status":"closed","first_seen_at":"2026-10-13T16:36:37Z","employer_posted_date":"2026-10-13","last_verified_at":"2026-10-21T20:14:10Z","board_verified":false,"closed_at":"2026-10-21T20:14:10Z","days_open":8,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":8},"description":"About this role\nAbout Global Fixed Income Team\nBlackRock’s active fixed income portfolio strategies stretch across a range of investment styles and segments of the fixed income universe. The breadth and depth of our platform puts us in a strong position to potentially deliver attractive returns in various market environments. With a focus on alpha generation and risk management, the team uses a top-down view from lead portfolio managers and bottom-up expertise from our sector specialists.\nResponsibilities:\nDesign and develop generative AI and machine learning solutions to address fixed income investment and business problems\n\nExperiment with and implement generative AI techniques such as retrieval-augmented generation (RAG), embeddings, and LLM-based workflows\n\nBuild, train, and fine-tune machine learning and deep learning models using appropriate frameworks and methodologies\n\nAnalyze large structured and unstructured datasets to extract insights, engineer features, and support model development\n\nApply statistical methods and hypothesis-driven experimentation to evaluate model performance and validate results\n\nWork closely with portfolio managers, researchers, and business stakeholders to translate investment problems into data science solutions\n\nContribute to the deployment and integration of models into production systems, including APIs and scalable pipelines\n\nCollaborate with data engineers to ensure high-quality data pipelines and efficient data access\n\nEnsure adherence to responsible AI principles including model interpretability, fairness, and data governance\n\nCommunicate model outputs, insights, and recommendations clearly to technical and non-technical stakeholders.\n\nStay updated with advancements in AI, machine learning, and quantitative methods to continuously enhance solutions\n\n Education and Qualifications/Skills:\nBachelor's or Master's degree in Computer Science/Engineering or related field.\n\n4+ years of relevant experience.\n\nGood understanding of the foundations and working principles of machine learning algorithms, linear algebra, probability theory, statistics, and optimization theory.\n\nKnowledge of at least one of the following domains: generative AI, statistical learning, optimization, NLP, deep learning or time series analysis.\n\nShould have strong proficiency in the following\n\nLanguages: Python, SQ\n\nFrameworks: PyTorch, TensorFlow, Scikit-learn, Hugging Face, LangChain, LlamaInde\n\nData & Storage: large-scale distributed data analytics engines, Pandas, Snowflake, FAISS, Pinecone, Chrom\n\nFamiliarity with cloud platforms (GCP, Azure, AWS\n\nProficiency in version control systems (e.g., Git/GitHub).\n\nStrong analytical thinking skills with an ability to creatively solve business problems, innovating new techniques as needed.\n\nExcellent verbal and written communication skills.\n\nSelf-driven and results oriented team player with ability to collaborate effectively across geographies/time zones\n\nPassion for solving interesting and relevant real-world problems in Finance using a data science and AI approaches.\n\nPrior experience in financial services or large-scale enterprise systems is a plus.\n\nOur benefits\nTo help you stay energized, engaged and inspired, we offer a wide range of benefits including a strong retirement plan, tuition reimbursement, comprehensive healthcare, support for working parents and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.\nOur hybrid work model\nBlackRock’s hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person - aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock.\n\nGuidance on AI use for candidates\nAt BlackRock, AI has long been part of how we work - enhancing decision-making, improving operations, and helping us deliver better outcomes for clients. We encourage candidates to use AI thoughtfully to learn, prepare, and work more effectively; but during our interview process, we want to focus on getting to know you through your own experiences, thinking, and judgment. To support you, we’ve provided guidance on when and how to use AI during our hiring process so you can approach each step with confidence and showcase your best self.\nAbout BlackRock\nAt BlackRock, we are all connected by one mission: to help more and more people experience financial well-being. Our clients, and the people they serve, are saving for retirement, paying for their children’s educations, buying homes and starting businesses. Their investments also help to strengthen the global economy: support businesses small and large; finance infrastructure projects that connect and power cities; and facilitate innovations that drive progress.\nThis mission would not be possible without our smartest investment - the one we make in our employees. It’s why we’re dedicated to creating an environment where our colleagues feel welcomed, valued and supported with networks, benefits and development opportunities to help them thrive.\nTo learn more about BlackRock, please visit Careers.BlackRock.com. We also encourage you to get to know us on LinkedIn, Instagram, YouTube, X, and TikTok.\nBlackRock is proud to be an Equal Opportunity Employer. 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