Experience
5 - 9 yrs
Job Location
Pune, India
Vacancy
2
Designation
Artificial Intelligence Engineer
Job Type
Not specified
Job Description
AI Engineer:
Key Responsiblities:
1. System Development: Designing and building AI models, such as neural networks, that learn from data and mimic human cognitive functions
2. Production Deployment: Transitioning research-level ML models into scalable, operational applications via APIs, microservices, or cloud platforms.
3. Data Handling & Training: Selecting, managing, and training models using large datasets, including natural language processing (NLP) and computer vision tasks.
4. Testing & Optimization: Evaluating accuracy, debugging, and improving AI performance to ensure systems run efficiently.
5. Collaboration: Working with data scientists and software engineers to align AI solutions with business objectives.
Required Skills and Qualifications:
1. Programming languages: Strong proficiency in Python, Java, or C++. How to use AI tooling to build up capability. Any UI/API automation framework.
2. ML Frameworks: Experience with TensorFlow, PyTorch, Keras, or Scikit-learn. How to use MCP server.
3. Data & Cloud Tools: Proficiency in SQL, Big Data Technologies, and cloud platforms like AWS SageMaker, Azure ML, or Google Cloud
4. Technical Skills: Expertise in machine learning, deep learning, NLP, computer vision, and algorithm development.
5. Education: Typically requires a Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
Key Responsiblities:
1. System Development: Designing and building AI models, such as neural networks, that learn from data and mimic human cognitive functions
2. Production Deployment: Transitioning research-level ML models into scalable, operational applications via APIs, microservices, or cloud platforms.
3. Data Handling & Training: Selecting, managing, and training models using large datasets, including natural language processing (NLP) and computer vision tasks.
4. Testing & Optimization: Evaluating accuracy, debugging, and improving AI performance to ensure systems run efficiently.
5. Collaboration: Working with data scientists and software engineers to align AI solutions with business objectives.
Required Skills and Qualifications:
1. Programming languages: Strong proficiency in Python, Java, or C++. How to use AI tooling to build up capability. Any UI/API automation framework.
2. ML Frameworks: Experience with TensorFlow, PyTorch, Keras, or Scikit-learn. How to use MCP server.
3. Data & Cloud Tools: Proficiency in SQL, Big Data Technologies, and cloud platforms like AWS SageMaker, Azure ML, or Google Cloud
4. Technical Skills: Expertise in machine learning, deep learning, NLP, computer vision, and algorithm development.
5. Education: Typically requires a Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.