Machine Learning Engineer

AI/ML Engineer (1–2 Years Experience)

Location: TAL, Bengaluru (Hybrid)

Experience: 1–2 Years

Department: R&D

Job Summary

We are seeking a highly motivated AI/ML Engineer with 1–2 years of experience in designing, developing, and deploying Machine Learning and Artificial Intelligence solutions. The candidate will work closely with data scientists, software engineers, and business stakeholders to develop intelligent systems, predictive models, and automation solutions that drive business value.

The ideal candidate should have hands-on experience in machine learning algorithms, data preprocessing, model training, evaluation, and deployment in production environments.

Key Responsibilities

AI/ML Development

• Design, develop, and optimize machine learning models for classification, regression, forecasting, recommendation, and anomaly detection applications.
• Implement AI algorithms using Python and popular ML frameworks.
• Perform data cleaning, preprocessing, feature engineering, and exploratory data analysis.
• Train, validate, and fine-tune machine learning and deep learning models.
• Develop and maintain AI pipelines for data ingestion, model training, and deployment.

Model Deployment & MLOps

• Deploy ML models into production environments using cloud or edge platforms.
• Monitor model performance and retrain models as required.
• Implement model versioning, experiment tracking, and performance monitoring.
• Collaborate with DevOps teams for CI/CD implementation of AI applications.

Data Engineering & Analytics

• Work with structured and unstructured datasets.
• Build automated data processing workflows.
• Develop dashboards and reports for model performance tracking.

Research & Innovation

• Stay updated with the latest advancements in AI, Machine Learning, Deep Learning, Generative AI, and Computer Vision technologies.
• Evaluate emerging AI technologies and propose innovative solutions.
• Contribute to proof-of-concept (PoC) projects and product development initiatives.

Collaboration

• Work closely with cross-functional teams including Software Development, Robotics, Product Management, and Business teams.
• Participate in code reviews and technical discussions.
• Document technical designs, algorithms, and implementation details.

Required Qualifications

Education

• Bachelor's or master's degree in Artificial Intelligence & Machine Learning, Electronics, Robotics, Information Technology or related field.

Technical Skills

• Strong programming skills in Python, C++, SQL.
• Understanding of Machine Learning algorithms:
• Linear Regression
• Logistic Regression
• Decision Trees
• Random Forest
• Support Vector Machines
• Clustering Algorithms
• Gradient Boosting Models
• Hands-on experience with:
• TensorFlow
• PyTorch
• Scikit-learn
• Pandas
• NumPy
• Knowledge of Deep Learning concepts:
• CNN
• RNN/LSTM
• Transformers
• Experience with SQL and database systems.
• Familiarity with Git version control.

Cloud & Deployment (Preferred)

• Exposure to AWS, Azure, or Google Cloud AI services.
• Basic understanding of Docker and Kubernetes.
• Knowledge of MLOps practices.

Preferred Skills

• Experience with Generative AI and Large Language Models (LLMs).
• Knowledge of Prompt Engineering and Retrieval-Augmented Generation (RAG).
• Exposure to Computer Vision applications using OpenCV.
• Understanding of NLP techniques and frameworks.
• Familiarity with robotics, autonomous systems, or industrial automation.
• Experience with REST APIs and microservices architecture.

Soft Skills

• Strong analytical and problem-solving abilities.
• Excellent communication and presentation skills.
• Ability to work independently and within cross-functional teams.
• Quick learner with a passion for AI innovation.
• Strong attention to detail and quality.

Key Performance Indicators (KPIs)

• Model accuracy and performance improvements.
• Successful deployment of AI solutions.
• Reduction in model inference latency.
• Automation and productivity improvements delivered.
• Code quality and adherence to development standards.
• Contribution to AI innovation initiatives.