Role Proficiency:

Independently develops error free code with high quality validation of applications guides other developers and assists Lead 1 – Software Engineering

Outcomes:

     Understand and provide input to the application/feature/component designs; developing the same in accordance with user stories/requirements.      Code debug test document and communicate product/component/features at development stages.      Select appropriate technical options for development such as reusing improving or reconfiguration of existing components.      Optimise efficiency cost and quality by identifying opportunities for automation/process improvements and agile delivery models      Mentor Developer 1 – Software Engineering and Developer 2 – Software Engineering to effectively perform in their roles      Identify the problem patterns and improve the technical design of the application/system      Proactively identify issues/defects/flaws in module/requirement implementation       Assists Lead 1 – Software Engineering on Technical design. Review activities and begin demonstrating Lead 1 capabilities in making technical decisions

Measures of Outcomes:

     Adherence to engineering process and standards (coding standards)      Adherence to schedule / timelines      Adhere to SLAs where applicable      Number of defects post delivery      Number of non-compliance issues      Reduction of reoccurrence of known defects      Quick turnaround of production bugs      Meet the defined productivity standards for project      Number of reusable components created   Completion of applicable technical/domain certifications Completion of all mandatory training requirements

Outputs Expected:

Code:

Develop code independently for the above

Configure:

Implement and monitor configuration process

Test:

Create and review unit test cases
scenarios and execution

Domain relevance:

Develop features and components with good understanding of the business problem being addressed for the client

Manage Project:

Manage module level activities

Manage Defects:

Perform defect RCA and mitigation

Estimate:

Estimate time
effort
resource dependence for one's own work and others' work
including modules

Document:

Create documentation for own work as well as perform peer review of documentation of others' work

Manage knowledge:

Consume and contribute to project related documents
share point
libraries and client universities

Status Reporting:

Report status of tasks assigned Comply with project related reporting standards/process

Release:

Execute release process

Design:

LLD for multiple components

Mentoring:

Mentor juniors on the team Set FAST goals and provide feedback to FAST goals of mentees

Skill Examples:

Explain and communicate the design / development to the customer Perform and evaluate test results against product specifications Develop user interfaces business software components and embedded software components 5 Manage and guarantee high levels of cohesion and quality6 Use data models Estimate effort and resources required for developing / debugging features / components Perform and evaluate test in the customer or target environment Team Player Good written and verbal communication abilities Proactively ask for help and offer help

Knowledge Examples:

     Appropriate software programs / modules      Technical designing      Programming languages      DBMS      Operating Systems and software platforms      Integrated development environment (IDE)      Agile methods Knowledge of customer domain and sub domain where problem is solved

Additional Comments:

Mandatory Skills: Python (NumPy, Pandas, Scikit-learn) PyTorch or TensorFlow for deep learning models Recommendation libraries (LightFM, Surprise) LangChain or AutoGPT for agentic AI development Hugging Face Transformers for NLP components Skill to Evaluate: python,pytorch,lightfm,langchain,huggingface Experience:3 to 6 Years Location:Bengaluru Job Description:Job Title: AIML Engineer Key Responsibilities: - Develop and implement machine learning algorithms and models for various applications, including computer vision, natural language processing, and recommendation systems. - Collaborate with cross-functional teams to identify business requirements and deliver innovative solutions. - Conduct research to stay up-to-date with the latest advancements in artificial intelligence and machine learning. - Analyze large datasets to evaluate model performance and refine algorithms for improved accuracy. - Participate in code reviews and contribute to maintaining high-quality code standards. - Create comprehensive documentation for models, algorithms, and processes. - Assist in deploying machine learning models in production environments. Skills and Tools Required: - Strong programming skills in languages such as Python, Java, or C++. - Solid understanding of machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. - Experience with data manipulation and analysis using tools like Pandas and NumPy. - Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) for model deployment and data storage. - Knowledge of algorithms and data structures. - Experience in computer vision, natural language processing, or reinforcement learning is a plus. - Excellent problem-solving skills and the ability to work collaboratively in a team. - Strong communication skills to present findings and technical concepts to non-technical stakeholders. - A degree in Computer Science, Data Science, or a related field, with relevant experience in AIML applications. This role provides an exciting opportunity to be part of a forward-thinking team at Sony India Software Centre, where you can make a significant impact through your expertise in artificial intelligence and machine learning. Education Qualificaiton: Advanced degree in Computer Science, Machine Learning, or related field Job Title: AIML Engineer Roles & Responsibilities: Key Responsibilities Design and implement ML-based personalization algorithms for product recommendations Develop agentic AI systems that can autonomously identify and solve customer support issues Create and optimize feature engineering pipelines for recommendation systems Build, test, and deploy ML models to production environments Collaborate with product and engineering teams to integrate ML solutions Monitor and improve model performance metrics Required Skills & Qualifications Advanced degree in Computer Science, Machine Learning, or related field 3+ years of experience building recommendation systems or personalization engines Experience with agentic AI development and autonomous systems Strong programming skills in Python and related ML frameworks Proven track record of deploying ML models to production Technology Stack Core ML/AI Technologies: Python (NumPy, Pandas, Scikit-learn) PyTorch or TensorFlow for deep learning models Recommendation libraries (LightFM, Surprise) LangChain or AutoGPT for agentic AI development Hugging Face Transformers for NLP components Preferred Experience Content Personalization such as Content ranking algorithms, User interest modelling, Content categorization and Engagement prediction Experience in Real-time Contextual Personalization, Location-based personalization, Time-aware recommendations and Device-specific adaptations Advanced Techniques such as Multi-modal recommendations (text, image, video), Knowledge graph-based recommendations, Explainable AI for recommendations and Reinforcement learning for personalization Privacy-First Personalization such as Edge computing for personalization, On-device machine learning, Federated learning implementations and Privacy-preserving recommendation techniques Project Details: As an AIML Engineer at, you will be responsible for designing, developing, and deploying advanced artificial intelligence and machine learning models to solve complex problems across various domains. You will work collaboratively with a team of data scientists, software engineers, and domain experts to create innovative solutions that enhance user experiences and optimize processes. Your role will involve researching new algorithms, implementing machine learning frameworks, and analyzing large datasets to extract meaningful insights.