AI/ML JD
Code: JFH 302
Varahi technologies pvt Ltd - AI/ML JD
• Company Type (Proprietor/Partnership/ Pvt. Ltd./LLP) :- pvt ltd
• Designation :- AI/ML
• Location :- Pirangut, Pune
• Salary :- Stipend 5,000 to 10,000 per month
• Gender:- Both
• Fresher / Experience :- Both
• No. of requirements :- 1
• Job timing :- 10am – 7pm
• Bond / Contract :- No
• WFH/WFO: WORK FROM OFFICE
• Interview Round : Google meet, Face to Face round, HR discussion
Job Description:
We are seeking a talented and motivated AI/ML Developer with a minimum of 2 years of experience to join our team. As an AI/ML Developer, you will be responsible for developing, implementing, and deploying machine learning models and algorithms to solve complex business problems. You will work closely with cross-functional teams to understand requirements, design solutions, and deliver high-quality software products.
Responsibilities:
Develop and deploy machine learning models and algorithms. Collaborate with data engineers and data scientists to preprocess and analyze data. Implement scalable and efficient solutions for real-world problems. Optimize existing machine learning models for performance and scalability. Stay updated with the latest advancements in AI/ML technologies and tools.
Requirements:
Bachelor's or Master's degree in Computer Science, Mathematics, or related field. Minimum of 2 years of hands-on experience in AI/ML development. Proficiency in Python and libraries such as TensorFlow, PyTorch, or scikit-learn. Solid understanding of machine learning algorithms and techniques. Experience with data preprocessing, feature engineering, and model evaluation. Strong problem-solving skills and attention to detail. Excellent communication and teamwork abilities.
Preferred Qualifications:
Experience with cloud platforms such as AWS, Azure, or Google Cloud. Familiarity with deep learning architectures and frameworks. Knowledge of software engineering best practices and version control systems. Experience with Docker and containerization technologies. Contributions to open-source projects or relevant publications.