What Jobs are available for Machine Learning Engineer in Delhi?
Showing 65 Machine Learning Engineer jobs in Delhi
Machine Learning Engineer
Posted 8 days ago
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Senior Machine Learning Engineer
Posted 2 days ago
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Senior Machine Learning Engineer
Posted 17 days ago
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Responsibilities:
- Design, develop, and implement advanced machine learning models and algorithms for diverse applications.
- Lead the entire ML lifecycle, including data collection, cleaning, feature engineering, model training, validation, and deployment.
- Collaborate with data scientists, software engineers, and product managers to define ML requirements and translate them into robust solutions.
- Optimize model performance for accuracy, efficiency, and scalability.
- Stay current with state-of-the-art ML research and techniques, and proactively identify opportunities for application.
- Develop and maintain ML infrastructure, tools, and pipelines.
- Conduct thorough model evaluation and A/B testing to ensure effectiveness and impact.
- Mentor and guide junior machine learning engineers and data scientists.
- Communicate complex technical concepts and findings to both technical and non-technical audiences.
- Contribute to the company's intellectual property through patents and publications.
- Master's or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related quantitative field.
- Minimum of 7 years of experience in machine learning engineering or a closely related role.
- Proven track record of successfully developing and deploying ML models in production environments.
- Deep understanding of various ML algorithms (e.g., deep learning, reinforcement learning, natural language processing).
- Proficiency in programming languages such as Python and experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
- Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (AWS, GCP, Azure).
- Strong understanding of software engineering best practices, including version control, testing, and CI/CD.
- Excellent analytical, problem-solving, and critical thinking skills.
- Strong communication and leadership abilities.
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Senior Machine Learning Engineer
Posted 21 days ago
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Key Responsibilities:
- Design, implement, and deploy machine learning models and algorithms for various applications.
- Develop and maintain scalable ML pipelines for data preprocessing, feature engineering, model training, and inference.
- Collaborate with data scientists to validate models and ensure their performance meets business requirements.
- Work with software engineers to integrate ML models into existing systems and products.
- Optimize model performance for efficiency, accuracy, and scalability.
- Conduct experiments to evaluate different modeling approaches and hyperparameter tuning.
- Stay updated on the latest advancements in machine learning and AI technologies.
- Document ML models, processes, and codebase thoroughly.
- Troubleshoot and resolve issues related to ML model deployment and performance.
- Mentor junior engineers and contribute to the team's knowledge sharing.
Qualifications:
- Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related quantitative field.
- Minimum of 5 years of experience in machine learning engineering or a related role.
- Strong proficiency in programming languages such as Python, Java, or Scala.
- Hands-on experience with ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn, XGBoost).
- Solid understanding of data structures, algorithms, and software engineering best practices.
- Experience with cloud platforms (e.g., AWS, Azure, GCP) and MLOps practices.
- Knowledge of big data technologies (e.g., Spark, Hadoop) is a plus.
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration abilities.
- Ability to work effectively in a hybrid team environment.
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Lead Machine Learning Engineer - NLP
Posted 2 days ago
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- Lead the design, development, and deployment of NLP models and systems.
- Mentor and guide a team of machine learning engineers.
- Conduct research into state-of-the-art NLP techniques and apply them to solve real-world problems.
- Optimize model performance, scalability, and efficiency.
- Collaborate with cross-functional teams to define project roadmaps and deliverables.
- Develop and maintain high-quality, production-ready code.
- Stay abreast of the latest advancements in AI and ML research.
- Master's or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field.
- Proven experience (7+ years) in machine learning, with a strong focus on NLP.
- Proficiency in Python and ML libraries (TensorFlow, PyTorch, Scikit-learn).
- Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices.
- Strong understanding of deep learning architectures relevant to NLP (e.g., Transformers, RNNs, LSTMs).
- Excellent problem-solving and analytical skills.
- Demonstrated leadership experience.
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Machine Learning Engineer - H&E Staining
Posted 8 days ago
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Job Title: H&E Image Analysis Scientist / Machine Learning Engineer- Spatial Omics (PhD)
Experience: Freshers
Location: Delhi
Job Description:
We are seeking a motivated PhD candidate interested in machine learning for histopathology
image analysis. The candidate will contribute to developing and optimizing deep learning
models to analyze digitized H&E slides for cancer classification and spatial mapping. This
role is well-suited for researchers aiming to apply advanced computational methods to
biomedical challenges.
Responsibilities:
● Design, develop, and train convolutional neural networks (CNNs) and related ML
models on H&E-stained histology images.
● Use and extend tools such as QuPath for cell annotations, segmentation models, and
dataset curation.
● Preprocess, annotate, and manage large image datasets to support model training
and validation.
● Collaborate with cross-disciplinary teams to integrate image-based predictions with
molecular and clinical data.
● Analyze model performance and contribute to improving accuracy, efficiency, and
robustness.
● Document research findings and contribute to publications in peer-reviewed journals.
Qualifications:
● PhD in Computer Science, Biomedical Engineering, Data Science, Computational
Biology, or a related discipline.
● Demonstrated research experience in machine learning, deep learning, or biomedical
image analysis (e.g., publications, thesis projects, or conference presentations).
● Strong programming skills in Python and experience with ML frameworks such as
TensorFlow or PyTorch.
● Familiarity with digital pathology workflows, image preprocessing/augmentation, and
annotation tools.
● Ability to work collaboratively in a multidisciplinary research environment.
Preferred:
● Background in cancer histopathology or biomedical image analysis.
● Knowledge of multimodal data integration, including spatial transcriptomics.
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Senior Machine Learning Engineer - Computer Vision
Posted 21 days ago
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Responsibilities:
- Design, develop, and implement advanced machine learning models for computer vision tasks.
- Conduct research and experimentation to advance state-of-the-art in image and video analysis.
- Lead the end-to-end machine learning project lifecycle, from data to deployment.
- Optimize model performance, scalability, and efficiency.
- Collaborate with cross-functional teams to define project requirements and deliver solutions.
- Stay current with the latest research and industry trends in AI and Computer Vision.
- Mentor junior machine learning engineers and contribute to knowledge sharing.
- Develop and maintain ML pipelines and MLOps practices.
- Evaluate and integrate new technologies and tools.
- Present research findings and project progress to stakeholders.
- Ph.D. or Master's degree in Computer Science, AI, Machine Learning, or a related quantitative field.
- 5+ years of experience in machine learning, with a strong focus on Computer Vision.
- Proven experience with deep learning frameworks (e.g., TensorFlow, PyTorch).
- Expertise in algorithms like CNNs, RNNs, Transformers for vision.
- Strong programming skills in Python and C++.
- Experience with large-scale data processing and distributed training.
- Familiarity with cloud platforms (AWS, GCP, Azure) and MLOps.
- Excellent analytical and problem-solving abilities.
- Strong communication and teamwork skills.
- Demonstrated ability to lead projects and mentor team members.
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Remote Senior Machine Learning Engineer - AI Innovation
Posted 16 days ago
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Lead AI Engineer - Machine Learning Operations
Posted 15 days ago
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Data Science Apprentice
Posted 25 days ago
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As a Data Science Apprentice, your responsibilities will include assisting senior data scientists in data collection, cleaning, and preprocessing. You will help in exploring datasets to identify patterns and insights using various statistical techniques. You will also support the development and testing of machine learning models under supervision. This role involves working with large datasets and utilizing programming languages like Python or R, along with relevant data science libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch).
You will gain exposure to data visualization tools and techniques to communicate findings effectively. The apprenticeship includes learning about experimental design, model evaluation, and deployment strategies. A strong analytical mindset, a curious nature, and a willingness to learn are paramount. You will participate in team meetings, contribute to project discussions, and present your findings to the team.
This is a fully remote apprenticeship, allowing you to work comfortably from your chosen location. We are looking for candidates who are eager to learn, possess strong problem-solving skills, and have a foundational understanding of statistics and programming. This program offers a clear pathway to potential full-time opportunities for high-performing apprentices. This is an ideal role for recent graduates or individuals looking to transition into the data science field.
Key Responsibilities:
- Assist in data cleaning, preprocessing, and feature engineering.
- Perform exploratory data analysis to uncover trends and insights.
- Support the development and testing of machine learning models.
- Utilize Python or R for data analysis and model building.
- Create data visualizations to communicate findings.
- Collaborate with senior data scientists on project tasks.
- Learn and apply data science methodologies and tools.
- Participate in code reviews and team discussions.
- Document analysis and model development processes.
- Bachelor's degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Economics, Engineering) or equivalent practical experience.
- Basic understanding of statistics, probability, and linear algebra.
- Familiarity with programming concepts, preferably in Python or R.
- Enthusiasm for data science and machine learning.
- Strong analytical and problem-solving skills.
- Excellent communication and teamwork abilities.
- Eagerness to learn and adapt in a remote environment.
- Previous exposure to data analysis tools or projects is a plus.
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