Technology Lead - AI engineer

Infosys is seeking an experienced AI Engineer to design, develop, and optimize scalable bigdata solutions. The candidate will work on building high-performance batch and real-time data pipelines leveraging the Hadoop ecosystem and distributed computing frameworks(Spark). The role involves working closely with data engineers, architects, and business stakeholders to deliver robust, scalable, and efficient data processing systems.Required Qualifications:Candidates authorized to work for any employer in Canada without employer-based visa sponsorship are welcome to apply. Infosys is unable to provide immigration sponsorship for this role at this time.Candidate must be located within commuting distance of Mississauga, Ontario or be willing to relocate to the areas.Bachelor’s degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.At least 4 years of Information Technology experience4+ years of experience in Big Data technologies.Required Qualifications : Develop data preparation tasks, while identifying patterns or anomalies. Ensure data readiness for advanced modeling. Develop models for complex use cases (e.g., forecasting models, LLM-based solutions), while refining algorithms to meet business needs, and ensure smooth deployment into scalable, production-ready solutions.Conduct testing and optimize algorithms for performance, reliability, and scalability, while providing guidance to team members in best practices. Design and develop predictive models and data-driven analyses to address business challenges. Build, evaluate, and deploy models, standardize code, and contribute to knowledge management. Leverage tools like SAS and R/Python to create reusable customizations for non-ML, ML, and deep learning algorithms, while enhancing analytics including LLMs, and create innovative, cost-effective solutions.Define analytics problems for projects; execute visualization, analysis, and predictive modeling under guidance. Proactively maintain models and implement improvements for accuracy and reliability. Apply governance controls to mitigate risks and ensure compliance. Analyze performance trends, recommend improvements, and document discrepancies for escalation. Maintain comprehensive documentation standards, while participating in knowledge transfer sessions. Participate in discussions with stakeholders to refine requirements, provide insights, and guide implementation of models. Apply the predefined quality measurement framework at an individual task level in the project. Deploy complex analytics tools or multi-system integration, while validating deployment success. Participate in developing scripts or templates for repeated deployments tasks. Contribute to analytic solutions, IP asset creation, and training initiatives. Contribute to thought leadership such as papers, innovative non-ML, ML, deep learning or LLM models, and proofs of concepts.Participate in and deliver analytics training, while contributing to content creation. Provide input for segment and unit-level business plans. Your contribution to the team: Deliver scalable, high-quality analytics solutions aligned to business needs. A knack for optimization, deployment and performance improvement of models. The ability to drive innovation through advanced analytics, automation and thought leadership. Enable team growth through knowledge sharing, training and standardization. Support business planning with data-driven insights.Nice to Have:Exposure to Machine Learning pipelines or MLOps workflows.Experience with Databricks platform.Experience with AWS/GCP.Estimated annual compensation range for the candidate based in the below location will be:Ontario: $ to $ The job entails sitting as well as working at a computer for extended periods of time. Should be able to communicate by telephone, email or face to face. Travel may be required as per the job requirements EEO Infosys provides equal employment opportunities to applicants and employees without regard to race; color; sex; gender identity; sexual orientation; religious practices and observances; national origin; pregnancy, childbirth, or related medical conditions; status as a protected veteran or spouse/family member of a protected veteran; or disability.