to lead the development and deployment of advanced machine learning models and AI solutions. The ideal candidate will have strong experience in data science, deep learning, and AI engineering, and will be responsible for designing intelligent systems that solve real-world business problems.
Key Responsibilities:
Design, build, and deploy scalable machine learning and deep learning models.
Work on projects involving supervised, unsupervised, and reinforcement learning.
Collect, clean, and preprocess large-scale structured and unstructured datasets.
Research and prototype cutting-edge AI techniques (e.g., NLP, computer vision, generative models).
Collaborate with data engineers, product managers, and software developers to integrate AI solutions into production.
Monitor and evaluate model performance, and implement improvements as needed.
Stay up-to-date with the latest AI/ML research, tools, and technologies.
Develop and maintain reusable ML pipelines and model lifecycle management.
Ensure ethical AI development practices, including model interpretability and fairness.
Required Qualifications:
Graduate BE/B.Tech and Postgraduate - MCA/MTech with specialization in computers /Electronics /IT or M.Sc.in CS/IT/Physics/Mathematics/Stats / Electronics
Language-: JS , Python , HTML5/CSS, Platform-: MySQL , PostgreSQL, Tools-: ML Tools and Libraries, Expertise-: API Integration Expert
3+ years of experience in AI/ML development and deployment
.
Proficiency in programming languages such as Python (e.g., scikit-learn, TensorFlow, PyTorch), R, or Julia.
Experience with deep learning frameworks (e.g., TensorFlow, Keras, PyTorch).
Strong understanding of statistics, linear algebra, and optimization techniques.
Experience with cloud platforms like AWS, GCP, or Azure.
Proficient in using data science tools and libraries (NumPy, Pandas, OpenCV, spaCy, Hugging Face, etc.).
Job Type: Contractual / Temporary
Contract length: 12 months
Pay: ?85,000.00 - ?90,000.00 per month
Benefits:
Provident Fund
Schedule:
Day shift
Work Location: In person
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