{"id":1242984,"url":"https://alion.io/job/rbc-generative-ai-data-scientist-ml-engineer","title":"Generative AI Data Scientist & ML Engineer","company":{"id":1757835,"name":"Royal Bank of Canada","domain":"rbc.com","url":"https://alion.io/company/rbc-com","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Phenom","truth_index":{"grade":"A","score":100,"open_postings":85,"ghost_share":0.024,"stale_share":0,"repost_share":0.035,"time_to_fill_p50_days":13,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Toronto, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":75000,"max_usd":136000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":56},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Bitbucket","optional":false},{"name":"C++","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GitHub","optional":false},{"name":"GitLab","optional":false},{"name":"Jupyter Notebook","optional":false},{"name":"Keras","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"MATLAB","optional":false},{"name":"Matplotlib","optional":false},{"name":"MySQL","optional":false},{"name":"NLP","optional":false},{"name":"NumPy","optional":false},{"name":"OpenCV","optional":false},{"name":"Pandas","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"PyTorch C++","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"TensorFlow C++","optional":false},{"name":"Time Series Forecasting","optional":false},{"name":"Transformers","optional":false},{"name":"Computer Vision","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-09-16T00:00:00Z","employer_posted_date":"2026-09-16","last_verified_at":"2026-10-18T03:48:20Z","board_verified":true,"closed_at":null,"days_open":32,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":32},"description":"Job Description\nWhat is the opportunity?\nAre you passionate about pushing the boundaries of artificial intelligence? Do you thrive in environments where innovation and cutting-edge research are at the forefront? We are offering an exciting opportunity to join our team as a Data Scientist / Researcher specializing in Generative AI Models. In this role, you will develop and optimize and use Large Language Models (LLM's), to solve complex problems and drive innovation in our AI solutions.\nWhat will you do?\nAs a researcher in this role, you will focus on the technical implementation and optimization of large language models (LLMs) to bring autonomous AI agents to life within a corporate setting. Your responsibilities will include:\nFine-Tune LLMs: Customize and optimize pre-trained LLMs for specific corporate applications, ensuring high performance and accuracy in various NLP tasks such as text classification, summarization, and entity recognition.\nVector Search Methodology: Develop and implement advanced vector search techniques, including the creation of efficient indexing and retrieval systems, to enhance the organization's ability to quickly and accurately access relevant information.\nAutonomous AI Agents: Design and build autonomous AI agents capable of performing complex tasks autonomously, such as customer service automation, data analysis, and decision-making support.\nData Preprocessing and Feature Engineering: Prepare and preprocess large datasets, perform feature extraction and engineering, and ensure data quality for training and validating models.\nModel Evaluation and Tuning: Conduct thorough evaluations of model performance using appropriate metrics and benchmarks. Perform hyperparameter tuning to optimize model configurations.\nAlgorithm Development: Research and implement novel algorithms and techniques to improve model efficiency, scalability, and robustness.\nDeployment and Integration: Work on deploying LLMs and AI agents into production environments, ensuring seamless integration with existing systems and workflows.\nContinuous Improvement: Monitor model performance in production, diagnose issues, and implement improvements and updates as needed to maintain and enhance model effectiveness.\nCollaborative Research: Collaborate with other data scientists, machine learning engineers, and domain experts to identify new opportunities for applying LLMs and AI agents, and contribute to joint research projects.\nDocumentation and Knowledge Sharing: Document your methodologies, experiments, and findings comprehensively, and share knowledge with the team through presentations, reports, and technical discussions.\nWhat do you need to succeed?\nMust-Have:\nEducational BackgroundPhD or Master's degree in Engineering, Computer Science, Data Science, or a related field.\n\n Research Experience8+ years of research experience in Engineering, Computer Science or related fields with a focus on machine learning applications.\nProven ability to handle and analyze large datasets (over terabytes of data) and deliver efficient models promptly.\n\n Technical SkillsProficient in Python and libraries such as NumPy, Pandas, Matplotlib, OpenCV, Scikit-Learn, TensorFlow, Keras, PyTorch, and PySpark.\nSkilled in C++, MATLAB, SQL (MySQL), and R.\nStrong understanding of machine learning techniques, including supervised and unsupervised learning, classification, decision trees, deep neural networks, CNNs, RNNs, AutoEncoders, GANs, and Transformers.\nExperience with regression modeling, time series analysis, data mining, data cleaning, and ETL processes.\n\nTools and PlatformsFamiliarity with GitLab, GitHub, Bitbucket, JIRA, VSCode, Jupyter Notebook, Spyder, and Eclipse.\nExperience with cloud platforms and tools such as Databricks, Azure Databricks, and AWS S3.\n\nAnalytical and Problem-Solving SkillsExceptional analytical abilities with a talent for identifying model weaknesses and optimizing performance.\nStrong initiative in approaching complex problems with innovative solutions.\n\nInterpersonal SkillsExcellent communication skills with the ability to lead and collaborate within cross-functional teams.\nProven organizational skills with the ability to manage multiple large-scale projects simultaneously.\n\nNice to Have:\nExperience in developing machine learning algorithms for video recognition and computer vision applications.\nBackground in high-energy physics research and familiarity with international laboratory environments like CERN or similar.\nPublished research in reputable journals and contributions to significant projects in the AI and physics communities.\nRecognition through awards or scholarships in related fields.\nWhat's in it for you?\nWork on groundbreaking AI projects that have a significant impact on the industry.\nBe part of a forward-thinking team that values creativity and innovation.\nOpportunities for continuous learning through training, workshops, and conferences.\nMentorship programs and career development plans to help you reach your goals.\nAttractive salary and benefits package that rewards your expertise and contributions.\nPerformance bonuses and recognition programs.\n Job Skills\nArtificial Intelligence (AI), Big Data Management, Data Mining, Data Science, Decision Making, Machine Learning (ML), Natural Language Processing (NLP), Predictive Analytics, Python (Programming Language), Statistical AnalysisAdditional Job Details\nAddress:\nRBC WATERPARK PLACE, 88 QUEENS QUAY W:TORONTOCity:\nTorontoCountry:\nCanadaWork hours/week:\n37.5Employment Type:\nFull timePlatform:\nPERSONAL & COMMERCIAL BANKINGJob Type:\nRegularPay Type:\nSalariedPosted Date:\n2026-09-09Application Deadline:\n2026-10-31Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above\nOur Employment Opportunities\nAt RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.\nJoin our Talent Community\nStay in-the-know about great career opportunities at RBC. Sign up and get customized info on our latest jobs, career tips and Recruitment events that matter to you.\nExpand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at jobs.rbc.com.\nRBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. 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