2,667 AI Engineer jobs in India
Lead AI Engineer - Deep Learning
Posted 22 days ago
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Job Description
Key Responsibilities:
- Lead the design, development, and implementation of deep learning models for various applications, including natural language processing, computer vision, and reinforcement learning.
- Collaborate with cross-functional teams, including product managers, data scientists, and software engineers, to define project requirements and deliver AI solutions.
- Research and evaluate state-of-the-art AI algorithms and techniques, and identify opportunities for their application.
- Develop robust, scalable, and efficient AI systems for deployment in production environments.
- Mentor and guide junior AI engineers, fostering a culture of learning, innovation, and technical excellence.
- Optimize model performance, troubleshoot complex issues, and ensure the reliability and accuracy of AI systems.
- Stay current with the latest advancements in AI research and development, and advocate for the adoption of new technologies.
- Contribute to the development of our AI strategy and roadmap.
- Write high-quality, well-documented code and contribute to code reviews.
- Present findings, progress, and technical solutions to stakeholders at various levels.
- Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Minimum of 8 years of experience in AI/ML development, with a strong focus on deep learning.
- Proven experience in leading AI projects and mentoring engineering teams.
- Expertise in deep learning frameworks such as TensorFlow, PyTorch, or Keras.
- Proficiency in programming languages like Python, with experience in relevant libraries (e.g., NumPy, SciPy, Pandas).
- Strong understanding of machine learning algorithms, statistical modeling, and data mining techniques.
- Experience with cloud platforms (e.g., AWS, Azure, GCP) and MLOps practices.
- Excellent problem-solving skills and the ability to tackle complex technical challenges.
- Strong communication and leadership skills, with the ability to effectively collaborate with diverse teams.
- Experience with large-scale data processing and distributed computing is a plus.
- Published research in top-tier AI conferences or journals is highly desirable.
Lead AI Engineer - Deep Learning Architect
Posted 17 days ago
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Job Description
Key Responsibilities:
- Lead the design, development, and implementation of advanced deep learning models and AI systems.
- Architect scalable and efficient AI solutions for various applications.
- Conduct research into emerging AI and machine learning trends and technologies.
- Develop and optimize deep learning algorithms for performance and accuracy.
- Mentor and guide a team of AI engineers, fostering a culture of innovation and technical rigor.
- Collaborate with product management and engineering teams to define AI project requirements and roadmaps.
- Deploy AI models into production environments and monitor their performance.
- Write clean, maintainable, and well-documented code in Python and relevant ML frameworks (TensorFlow, PyTorch).
- Stay updated with the latest advancements in AI and machine learning research.
Qualifications:
- M.S. or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- 5+ years of hands-on experience in developing and deploying deep learning models.
- Proven experience in leading AI engineering teams.
- Expertise in Python and deep learning frameworks such as TensorFlow, PyTorch, or Keras.
- Strong understanding of various deep learning architectures (CNNs, RNNs, Transformers, etc.).
- Experience with cloud platforms (AWS, GCP, Azure) and MLOps practices.
- Excellent problem-solving, analytical, and communication skills.
- Demonstrated ability to work effectively in a remote team environment.
Lead AI/ML Engineer - Deep Learning
Posted today
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Location: Fully remote, based in or able to work within India.
Senior AI/ML Engineer - Deep Learning
Posted 6 days ago
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Job Description
Responsibilities:
- Design, build, and train deep learning models for various applications (e.g., computer vision, natural language processing, predictive analytics).
- Develop and implement scalable machine learning pipelines using Python and relevant frameworks (TensorFlow, PyTorch, Keras).
- Collaborate with data scientists, software engineers, and product managers to define project requirements and deliver AI-powered solutions.
- Conduct thorough data analysis, feature engineering, and model evaluation.
- Deploy trained models into production environments and monitor their performance.
- Research and stay up-to-date with the latest advancements in AI, machine learning, and deep learning.
- Optimize model performance for accuracy, efficiency, and scalability.
- Contribute to the development of AI/ML best practices and MLOps strategies.
- Mentor junior engineers and share knowledge within the team.
- Document model architectures, algorithms, and experimental results.
- Identify opportunities to leverage AI/ML to drive business value and innovation.
- Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Minimum of 5 years of experience in AI/ML engineering, with a strong focus on deep learning.
- Proven experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras.
- Proficiency in Python and strong software engineering skills.
- Experience with cloud platforms (AWS, Azure, GCP) and ML services.
- Solid understanding of machine learning algorithms, statistical modeling, and data mining techniques.
- Experience with data preprocessing, feature selection, and model evaluation.
- Familiarity with MLOps principles and tools for model deployment and monitoring.
- Excellent problem-solving, analytical, and critical thinking skills.
- Strong communication and collaboration skills, able to articulate complex technical concepts clearly.
- Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
AI/ML Engineer - Deep Learning Specialist
Posted 8 days ago
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Senior AI/ML Engineer - Deep Learning
Posted 8 days ago
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Job Description
Key Responsibilities:
- Design, develop, train, and deploy advanced deep learning models for various applications, including computer vision, natural language processing, and predictive analytics.
- Conduct research on state-of-the-art AI and ML techniques, identifying opportunities for implementation and innovation.
- Develop and maintain robust machine learning pipelines for data processing, feature engineering, model training, and evaluation.
- Utilize deep learning frameworks such as TensorFlow, PyTorch, and Keras to build and optimize models.
- Work with large datasets, ensuring data quality, integrity, and efficient processing.
- Collaborate with software engineers and product managers to integrate AI/ML solutions into production systems.
- Evaluate model performance, identify areas for improvement, and implement optimization strategies.
- Stay current with the latest research papers, industry trends, and emerging technologies in AI/ML.
- Mentor junior engineers and contribute to the team's technical growth and knowledge sharing.
- Document technical designs, methodologies, and experimental results comprehensively.
- Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related quantitative field.
- Minimum of 5-7 years of progressive experience in AI/ML engineering, with a strong emphasis on deep learning.
- Proven track record of developing and deploying deep learning models in real-world applications.
- Expertise in deep learning architectures (e.g., CNNs, RNNs, Transformers) and their applications.
- Proficiency in programming languages such as Python and experience with ML libraries/frameworks (TensorFlow, PyTorch, Scikit-learn).
- Strong understanding of machine learning principles, algorithms, and statistical modeling.
- Experience with data processing, feature engineering, and model evaluation techniques.
- Excellent analytical, problem-solving, and critical thinking skills.
- Strong communication and collaboration skills, with the ability to explain complex technical concepts clearly.
- Experience with cloud platforms (AWS, Azure, GCP) and MLOps is a plus.
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Remote AI/ML Engineer - Deep Learning
Posted 8 days ago
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Senior AI/ML Engineer - Deep Learning
Posted 10 days ago
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Job Description
Key Responsibilities:
- Design, implement, and optimize deep learning models for tasks such as computer vision, natural language processing, and predictive analytics.
- Conduct research and development to explore new AI algorithms and techniques.
- Develop robust and scalable machine learning pipelines for data preprocessing, model training, and deployment.
- Collaborate with data scientists and software engineers to integrate AI models into product offerings.
- Evaluate model performance, identify areas for improvement, and implement enhancements.
- Stay current with the latest advancements in AI, machine learning, and deep learning research.
- Contribute to the technical roadmap and strategy for AI initiatives.
- Mentor junior engineers and share knowledge within the team.
- Document research findings, model architectures, and deployment procedures.
Qualifications:
- Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- 5+ years of experience in developing and deploying machine learning and deep learning models in a production environment.
- Proficiency in Python and experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras.
- Strong understanding of machine learning algorithms, statistical modeling, and data mining techniques.
- Experience with cloud platforms (AWS, Azure, GCP) and big data technologies.
- Excellent problem-solving skills and the ability to tackle complex technical challenges.
- Strong communication and teamwork skills, with the ability to explain technical concepts to non-technical audiences.
- Proven track record of contributing to significant AI/ML projects.
AI/ML Engineer - Deep Learning Specialist
Posted 13 days ago
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Job Description
Key responsibilities involve staying abreast of the latest advancements in AI and deep learning research, translating research findings into practical applications, and collaborating closely with software engineers and data scientists. You will be expected to experiment with various neural network architectures (e.g., CNNs, RNNs, Transformers), optimize model performance for efficiency and accuracy, and implement robust ML pipelines. Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices for deploying and managing models in production environments is highly desirable. The ideal candidate will possess strong programming skills (Python preferred), a solid understanding of linear algebra, calculus, and probability, and demonstrable experience with deep learning libraries such as TensorFlow or PyTorch. Excellent problem-solving abilities, a passion for innovation, and strong communication skills are essential for this dynamic role. This hybrid position offers the opportunity to collaborate in person while also benefiting from remote flexibility.
Responsibilities:
- Design, develop, and implement deep learning models.
- Work with large datasets for training and validation.
- Conduct research on cutting-edge AI/ML techniques and algorithms.
- Optimize model performance and efficiency for production deployment.
- Collaborate with cross-functional teams to integrate AI solutions.
- Implement and maintain machine learning pipelines and MLOps practices.
- Evaluate and benchmark model performance using various metrics.
- Stay current with industry trends and advancements in AI and deep learning.
- Contribute to technical documentation and knowledge sharing.
- Troubleshoot and resolve issues related to AI model development and deployment.
Qualifications:
- Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Minimum of 4 years of hands-on experience in developing and deploying deep learning models.
- Proficiency in Python and deep learning frameworks (e.g., TensorFlow, PyTorch, Keras).
- Strong understanding of machine learning algorithms, neural networks, and statistical modeling.
- Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
- Familiarity with MLOps principles and tools.
- Excellent analytical, problem-solving, and critical thinking skills.
- Strong communication and teamwork abilities.
Explore opportunities in the rapidly growing field of AI engineering. This domain involves developing, testing, and deploying artificial intelligence models and systems. AI engineers work with machine learning, deep learning, and