Ai Ml Engineer

Position Title: AI/ML Engineer

Department: Data Science

Reports To: AI/ML Team Lead

Work Location: Electronic City, Bengaluru, India

Position Summary:

• The Data Scientist should possess a strong background in data analysis, machine learning, and statistical modeling.

Essential Duties and Responsibilities:

• The essential duties of the position include the following, and other duties may be assigned
• Develop processes, techniques, and tools to analyze and monitor, evaluate model
  performance.
• Envision, implement, and deliver production-level models.
• Owning the definition of data architecture components.
• Producing and approving conceptual, logical, and physical architecture diagrams.
• Own the delivery of AI/ML modules.
• Own the AI/ML module integration with other in-house applications. Build various NLP
  models for different applications from scratch.
• Build recommendation systems from scratch with images and text.
• Build expression analysis models with webcam input to understand emotions.
• Build various ML models supporting Psychometric analysis from scratch.
• Set up and manage AI/ML development and deployment in production infrastructure.
• Identify transfer learning possibilities and build new training datasets wherever required.
• Efficiently communicate with business stakeholders to make them understand AI/ML
• results and limitations and set the right timeline.
• Take responsibility for projects and work with minimal guidance/training.
• Stay updated about the latest AI/ML research relevant to our domain

Qualifications:

• To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Education/Experience:

• Experience or knowledge in programming and handling data of various forms and sizes. Experience or knowledge in programming and handling data of various forms and sizes. Experience in building out data infrastructure and A/B testing platforms. Deep understanding of structured and unstructured data. Hands-on experience with Graph DB (Neo4J) etc. is a plus. Ability to use data visualization tools like D3, GG Plot, Plotly, Piplot etc. Experience in working with large and sparse data sets. Hands-on experience in semantic search. At least 5 years of hands-on experience in various models on NLP, CNN, RNN, LSTM, Transformer-based Clustering, Reinforcement Learning, Regression, etc. Must have extensive knowledge of CV2, TensorFlow, PyTorch, Keras, and other deep-learning libraries. Must have strong mathematical and statistical knowledge. Must have good knowledge of NLP to contribute to ongoing projects. Good knowledge of image classifiers, image captioning, image segmentation, and object detection. Good understanding of attention mechanisms, activation functions, feature engineering, transformers (BERT, S-BERT), and recommendation systems. Added advantage in understanding various databases, APIs, and file formats like JSON, PARQUET, and XML.
• Must have hands-on SQL experience. Good communication skills, able to handle projects alone or as a team.

Language Ability:

• Proficient in articulating complex AI/ML concepts to both technical and non-technical stakeholders.
• Strong written communication skills to document processes, models, and architecture clearly and concisely. Comfortable presenting findings and recommendations to business leaders and cross-functional teams.

Math Ability:

• Expertise in linear algebra, calculus, probability, and statistics to support the development and evaluation of AI/ML models. Strong aptitude for understanding and applying concepts like optimization techniques and Bayesian inference. Proven ability to design and analyze algorithms for large-scale datasets.

Reasoning Ability:

• Exceptional critical thinking skills to evaluate model performance, troubleshoot issues, and optimize results. Ability to conceptualize and define data architecture and workflows tailored to business objectives. Strong problem-solving skills, particularly in novel domains like emotion analysis, recommendation systems, and psychometrics. Capability to assess transfer learning possibilities and develop solutions with minimal oversight.

Computer Skills:

• Proficiency in Python, R, or other relevant programming languages for AI/ML development. Advanced skills in NLP frameworks (e.g., spaCy, Hugging Face) and ML libraries (e.g., TensorFlow, PyTorch). Experience with production-level deployment of AI/ML models and managing their infrastructure. Skilled in designing and approving architecture diagrams and integrating AI/ML modules with in-house systems. Familiarity with cloud platforms (AWS, Azure, or GCP) for AI/ML deployment and operations. Knowledge of version control systems (e.g., Git) and CI/CD pipelines