Machine Learning Engineer

3 weeks ago

india Talent Hub Acquisition Resource LLP Full time


Machine Learning Engineer

Type: Full-Time 

Experience: Minimum 4+ years in AI ML

Location: Bangalore, Mumbai & Delhi

Work type: Currently Remote


Job Summary: 

As a Machine Learning Engineer, you will be at the forefront of cutting-edge machine learning technologies. You will collaborate with a multi-disciplinary team of researchers, software engineers, and data scientists to develop, implement, and deploy machine learning models to solve complex problems. 


Key Responsibilities:


Large Language Model (LLM) Expertise:

  • Model Architecture and Design: Familiar with foundational LLM architectures like Transformers, GPT, and BERT. Understands attention mechanisms, positional encodings, and other critical components.
  • Pre-trained LLM Deployment: Proficient in deploying models like GPT-4 and BERT, optimizing with techniques such as quantization and distillation.
  • Fine-tuning Expertise: Experienced in customizing LLMs for specific tasks using strategies like few-shot learning and transfer learning.
  • Training from Scratch: Skilled in curating diverse datasets, handling distributed training, maintaining model stability, and optimizing hyperparameters.

Research and Algorithm Development:

  • Collaborate with data scientists to conceptualize machine learning strategies.
  • Design and implement machine learning algorithms ensuring fairness and interpretability.

Data Management and Preprocessing:

  • Oversee data acquisition, storage, and distribution, ensuring quality and privacy compliance.
  • Perform data preprocessing, including normalization, transformation, and feature engineering.

Model Implementation and Validation:

  • Develop models using frameworks like TensorFlow or PyTorch, focusing on scalability and efficiency.
  • Implement rigorous validation processes like cross-validation and A/B testing.

Optimization and Scaling:

  • Optimize models for computational efficiency and accuracy.
  • Collaborate with infrastructure engineers to scale models for large datasets and high-throughput requirements.

Deployment:

  • Translate research algorithms into production-level code for integration into platforms.
  • Work with DevOps teams to deploy models in a cloud environment, ensuring maintainability and scalability.

Performance Monitoring and Maintenance:

  • Develop tools to monitor model performance and address degradation or anomalies.
  • Update models based on performance metrics or new data.

Collaboration and Communication:

  • Collaborate with stakeholders, developers, and engineers to integrate ML solutions.
  • Articulate machine learning concepts and model outcomes to non-technical stakeholders.

Continued Learning and Mentorship:

  • Stay updated with the latest research and trends in machine learning.
  • Mentor junior engineers and interns, sharing knowledge and best practices.


Qualifications: 

Required: 

● Bachelor’s Degree in Computer Science, Engineering, Statistics, or a related field.

● Minimum of 5 years of experience in machine learning or a related field.

● Strong programming skills in Python, C++, or other relevant languages.

● Experience with machine learning frameworks such as TensorFlow, PyTorch, or similar.

● Strong knowledge of machine learning algorithms and principles. 

● Proven expertise in handling, training, and deploying Large Language Models (LLMs).

● Experience with cloud computing services (AWS, Azure, GCP, etc.).

● Solid understanding of software engineering best practices. 

● Exceptional problem-solving abilities. 

● Excellent communication skills, both written and verbal.

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