On-Site
Full-Time
Mumbai, Maharashtra
India
Skills
Large Language Models (LLM)
Natural Language Processing (NLP)
Machine Learning
About the Role
Job Description:
Collaborate with cross-functional teams to understand project requirements and objectives.
Assist in data collection, preprocessing, and cleaning for training ML models.
Develop, train, and evaluate machine learning models in NLP, speech to text and text to speech.
Implement and deploy ML models into production systems.
Process automation and integration into the third-party platforms with focus on financial services platforms.
Monitor and optimize the performance of deployed models.
Conduct experiments to fine-tune algorithms and improve model accuracy.
Stay updated with the latest trends, tools, and technologies in the ML space.
Minimum Qualifications and Experience:
Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field with a minimum of 3-4 years of experience.
Required Expertise:
Strong understanding of fundamental ML concepts, algorithms, and techniques (e.g., supervised, unsupervised learning).
Proficiency in programming languages such as Python or R.
Familiarity with ML libraries/frameworks like TensorFlow, PyTorch, or scikit-learn.
Knowledge of data manipulation and analysis using tools like Pandas and NumPy.
Familiarity with cloud platforms (e.g., AWS, Google Cloud, or Azure).
Understanding of database systems (SQL or NoSQL).
Experience with version control systems like Git.
Basic knowledge of software engineering principles.
Problem-solving and critical thinking.
Strong communication and collaboration skills.
Eagerness to learn and adapt in a fast-paced environment.
Collaborate with cross-functional teams to understand project requirements and objectives.
Assist in data collection, preprocessing, and cleaning for training ML models.
Develop, train, and evaluate machine learning models in NLP, speech to text and text to speech.
Implement and deploy ML models into production systems.
Process automation and integration into the third-party platforms with focus on financial services platforms.
Monitor and optimize the performance of deployed models.
Conduct experiments to fine-tune algorithms and improve model accuracy.
Stay updated with the latest trends, tools, and technologies in the ML space.
Minimum Qualifications and Experience:
Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field with a minimum of 3-4 years of experience.
Required Expertise:
Strong understanding of fundamental ML concepts, algorithms, and techniques (e.g., supervised, unsupervised learning).
Proficiency in programming languages such as Python or R.
Familiarity with ML libraries/frameworks like TensorFlow, PyTorch, or scikit-learn.
Knowledge of data manipulation and analysis using tools like Pandas and NumPy.
Familiarity with cloud platforms (e.g., AWS, Google Cloud, or Azure).
Understanding of database systems (SQL or NoSQL).
Experience with version control systems like Git.
Basic knowledge of software engineering principles.
Problem-solving and critical thinking.
Strong communication and collaboration skills.
Eagerness to learn and adapt in a fast-paced environment.