4,039 Autonomous Driving Systems jobs in India

About the Role:

We are seeking a highly skilled and experienced Machine Learning Engineer to join our dynamic team. As a Machine Learning Engineer, you will be responsible for the design, development, deployment, and maintenance of machine learning models and systems that drive our (mention specific business area or product, e.g., recommendation engine, fraud detection system, autonomous vehicles). You will work closely with data scientists, software engineers, and product managers to translate business needs into scalable and reliable machine learning solutions. This is a key role in shaping the future and requires a strong technical foundation combined with a passion for innovation and problem-solving.

Responsibilities:

Model Development & Deployment:

• Design, develop, and deploy machine learning models using various algorithms (e.g., regression, classification, clustering, deep learning) to solve complex business problems.
• Select appropriate datasets and features for model training, ensuring data quality and integrity.
• Implement and optimize model training pipelines, including data preprocessing, feature engineering, model selection, and hyperparameter tuning.
• Deploy models to production environments using containerization technologies (e.g.,Docker, Kubernetes) and cloud platforms (e.g., AWS, GCP, Azure).
• Monitor model performance in production, identify and troubleshoot issues, and implement model retraining and updates as needed.

Infrastructure & Engineering:

• Develop and maintain APIs for model serving and integration with other systems.
• Write clean, well-documented, and testable code.
• Collaborate with software engineers to integrate models into existing products and services.

Research & Innovation :

• Stay up to date with the latest advancements in machine learning and related technologies.
• Research and evaluate new algorithms, tools, and techniques to improve model performance and efficiency.
• Contribute to the development of new machine learning solutions and features.
• Proactively identify opportunities to leverage machine learning to solve business challenges.

Collaboration & Communication:

* Collaborate effectively with data scientists, software engineers, product managers, and other stakeholders.

* Communicate technical concepts and findings clearly and concisely to both technical and non-technical audiences.

* Participate in code reviews and contribute to the team's knowledge sharing.

Qualifications:

* Experience : 7+ years of experience in machine learning engineering or a related field.

Technical Skills:

• Programming Languages : Proficient in Python and experience with other languages (e.g., Java, Scala, R) is a plus.
• Machine Learning Libraries : Strong experience with machine learning libraries and frameworks such as scikit-learn, TensorFlow, PyTorch, Keras, etc.
• Data Processing : Experience with data manipulation and processing using libraries like Pandas, NumPy, and Spark.
• Model Deployment : Experience with model deployment frameworks and platforms (e.g., TensorFlow Serving, TorchServe, Seldon, AWS SageMaker, Google AI Platform, Azure Machine Learning).
• Databases : Experience with relational and NoSQL databases (e.g., SQL, MongoDB, Cassandra).
• Version Control : Experience with Git and other version control systems.
• DevOps : Familiarity with DevOps practices and tools.
• Strong understanding of machine learning concepts and algorithms : Regression, Classification, Clustering, Deep Learning etc.

Soft Skills:

• Excellent problem-solving and analytical skills.
• Strong communication and collaboration skills.

Job Description Machine Learning Engineer

We seek a motivated and enthusiastic Machine Learning Engineer to join our team. As a fresher, you will work closely with senior engineers and data scientists to learn, grow, and contribute to various machine learning projects. You will help in building, training, and optimizing machine learning models and work with data to derive meaningful insights. This role is perfect for someone looking to start a career in machine learning, with opportunities for continuous learning and growth.

Key Responsibilities:

• Assist in developing machine learning models : Collaborate with senior engineers to design and build machine learning models for real-world applications.
• Data preprocessing : Work on cleaning, transforming, and organizing datasets to prepare them for model training.
• Model evaluation : Help evaluate models using different metrics and assist in tuning hyperparameters to optimize performance.
• Research and learning : Stay updated on the latest machine learning techniques and best practices through independent learning and team mentorship.
• Collaborate with teams : Work closely with data scientists, data engineers, and product teams to understand project requirements and assist in solution development.
• Documentation : Contribute to project documentation, including code comments, model descriptions, and reports.
• Support model deployment : Assist in integrating models into production systems and monitor their performance over time.
• Debugging and troubleshooting : Help identify and resolve issues in data processing pipelines and model performance.

Qualifications:

• Education : Bachelor’s /Master’s degree in Computer Science, Machine learning, Data Science, Mathematics, Statistics, or a related field (or equivalent experience).
• Skills :
• Basic understanding of machine learning algorithms (e.g., linear regression, decision trees, k-means clustering).
• Familiarity with programming languages such as Python or R.
• Knowledge of machine learning libraries such as TensorFlow, PyTorch, or Scikit-learn.
• Experience with data manipulation tools like Pandas and NumPy.
• Good problem-solving and analytical skills.
• Strong desire to learn and grow in the machine learning field.
• Effective communication and teamwork skills.

Preferred Qualifications:

• Internship or coursework in machine learning, artificial intelligence, or data science.
• Experience with projects involving machine learning (academic or personal).
• Familiarity with cloud platforms like AWS, Google Cloud, or Azure is a plus.
• Exposure to tools like Jupyter Notebooks, Git, and version control systems.

Benefits:

• Competitive entry-level salary.
• Learning and development opportunities, including mentorship from senior engineers.
• Flexible work environment with opportunities for remote work.
• Access to industry-leading tools and technologies.

Role - MLOps

Location - Remote

Experience - 5 + Yrs

Responsibilities:

● Build and optimize model serving infrastructure with a focus on inference latency and cost

optimization

● Architect efficient inference pipelines that balance latency, throughput, and cost across

various acceleration options

● Develop monitoring and observability solutions for ML systems

● Collaborate with ML Engineers to establish best practices for optimized model deployment

● Implement cost-efficient, enterprise-scale solutions

● Collaborate in a cross-functional, distributed team for continuous system improvement

● Work with MLEs, QA Engineers, and DevOps Engineers

● Evaluate and implement new technologies and tools

● Contribute to architectural decisions for distributed ML systems

Experience and Qualifications:

● 5+ years of experience in software engineering with Python

● Experience with ML frameworks, particularly PyTorch

● Experience optimizing ML models with hardware acceleration (AWS Neuron , ONNX,

TensorRT)

● Experience with AWS ML services and hardware-accelerated instances (Sagemaker,

Inferentia, Trainium)

● Proven experience building and operating AWS serverless architectures

● Deep understanding of event-driven processing patterns, SQS/SNS and serverless caching

solutions

● Experience with containerization using Docker and orchestration tools

● Strong knowledge of RESTful API design and implementation

● Proficiency in writing good quality & secure code and be familiar with static code analysis

tools

● Excellent analytical, conceptual and communication skills in spoken and written English

● Experience applying Computer Science fundamentals in algorithm design, problem solving,

and complexity analysis

Job Summary:

We are looking for highly motivated and analytical Machine Learning Engineers with 1–3 years of experience in building scalable, production-ready AI/ML models. This role involves working on complex business problems using advanced ML/DL techniques across domains such as Natural Language Processing (NLP), Computer Vision, Time Series Forecasting, and Generative AI.

You will be responsible for end-to-end model development, deployment, and performance tracking while collaborating with cross-functional teams including data engineering, DevOps, and product.

Location: Noida / Gurugram / Indore / Bengaluru / Pune / Hyderabad

Experience: 1–3 Years

Education: BE / B.Tech / M.Tech / MCA / M.Com

Key Responsibilities:

Model Development & Experimentation

• Design and build machine learning models for NLP, computer vision, and time series prediction using supervised, unsupervised, and deep learning techniques.
• Conduct experiments to improve model performance via architectural modifications, hyperparameter tuning, and feature selection.
• Apply statistical analysis to validate and interpret model results.
• Evaluate models using appropriate metrics (e.g., accuracy, precision, recall, F1-score, AUC-ROC).

Data Handling & Feature Engineering

• Process large structured and unstructured datasets using Python, Pandas, and DataFrame APIs.
• Perform feature extraction, transformation, and selection tailored to specific ML problems.
• Implement data augmentation and enrichment techniques to enhance training quality.

Model Deployment & Productionization

• Deploy trained models to production environments using cloud platforms such as AWS (especially SageMaker).
• Containerize models using Docker and orchestrate deployments with Kubernetes.
• Implement monitoring, logging, and automated retraining pipelines for model health tracking.

Collaboration & Innovation

• Collaborate with data engineers and architects to ensure smooth data flow and infrastructure alignment.
• Explore and adopt cutting-edge AI/ML methodologies and GenAI frameworks (e.g., LangChain, GPT-3).
• Contribute to documentation, versioning, and knowledge-sharing across teams.
• Drive innovation and continuous improvement in AI/ML delivery and engineering practices.

Mandatory Technical Skills:

• Languages & Tools: Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch)
• Model Development: Deep Learning, NLP, Time Series, Computer Vision
• Cloud Platforms: AWS (especially SageMaker)
• Model Deployment: Docker, Kubernetes, REST APIs
• ML Ops: Model monitoring, performance logging, CI/CD
• Frameworks: LangChain (for GenAI), Transformers, Hugging Face

Preferred / Good to Have:

• Experience with Foundation Model tuning and prompt engineering
• Hands-on with Generative AI (GPT-3/4, OpenAI APIs, LangChain integrations)
• Certifications: AWS Certified Machine Learning – Specialty
• Experience with version control (Git), and experiment tracking tools (MLflow, Weights & Biases)

Soft Skills:

• Excellent communication and presentation abilities
• Strong analytical and problem-solving mindset
• Ability to work in collaborative, fast-paced environments
• Curiosity to learn emerging technologies and apply them to real-world problems