Highlights:
2.00 - 5.00 Years
9.00 - 20.00 INR (Lacs)/Yearly
Full time
Full time
Roles & Responsibility
'Deploying AI/ML solution to productions and generating value from it.
Developing End-to-End solutions with teammates and working with stakeholders, data team, business team and product team.
Helping dev-ops team to deploy and integrate solution with existing systems
Data Quality and Availability: Ensuring the quality and availability of data for model training and validation can be a significant challenge. This includes dealing with missing, unstructured, or inconsistent data.
Model Performance: Developing models that perform well in real-world scenarios is a complex task. It requires rigorous testing, validation, and continuous optimization.
Scalability: Scaling AI solutions to handle large volumes of data and integrate with various business functions can be technically challenging.
Keeping Up with Rapid Advances: The field of AI is advancing rapidly. Keeping up with the latest research, techniques,
and tools can be demanding.
Ethical and Regulatory Compliance: Ensuring that AI models are transparent, fair, and comply with all relevant regulations and ethical guidelines is a critical challenge. This includes understanding and mitigating potential biases in AI models.
Requirements:
Functional Skills:
'Working knowledge of Data Science toolbox like: Python, SQL, Jupyter Notebook, Azure/AWS cloud, PySpark, TensorFlow, PyTorch, Keras, and other Big Data toolkit
Deep understanding of AI/ML models with experience in LLM, Reinforcement Learning, Computer Vision, and Deep Learning
Expertise in NLP, Computer Vision, Speech technology(STT, TTS)
Behavioural Skills:
'Ability to connect technology with business goals and outcomes.
A hustler who constantly likes to go into design-build-deploy cycle for innovative new idea
A Problem solving mindset for trying out recent ideasResult orientation with execution
📌 Data Scientist Diverse Global Solutions Provider Corp Mumbai
🏢 Skyleaf Consultants
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