Machine Learning Engineer

Job Description:
We are seeking an experienced Senior NLP Engineer with a strong background in machine learning to join our growing team. As a Senior NLP Engineer, you will play a pivotal role in developing and enhancing our NLP-powered applications and machine learning models. You will have the opportunity to work on exciting projects that leverage the power of NLP and machine learning to solve complex problems and improve user experiences.

Key Roles and Responsibilities:
Roles -
•    Leader: Responsible for leading the team and setting a positive example. They should be able to motivate and inspire their team members to achieve their goals.
•    Strategist: Should be able to develop and execute a clear and concise strategy for the team. This includes identifying and prioritizing data science opportunities, and developing project plans that align with the organization's overall goals.
•    Communicator: Should be able to communicate effectively with both technical and non-technical audiences. They should be able to explain complex data science concepts in a clear and concise way.
•    Mentor: Able to mentor and develop their team members. This includes providing guidance and support on technical and professional matters.

Areas of Expertise -
1.    NLP Model Development: Develop, implement, and fine-tune NLP models for a variety of applications, including text classification, semantic similarity searches, named entity recognition, and chatbots.
2.    Machine Learning: Design, train, and evaluate machine learning models to enhance NLP solutions, including deep learning approaches such as transformers.
3.    Data Preprocessing: Handle data preprocessing tasks, such as text cleaning, tokenization, and feature engineering, to optimize model performance.
4.    Feature Engineering: Extract and engineer meaningful features from text data to improve model accuracy and efficiency.
5.    Evaluation and Optimization: Continuously assess model performance, fine-tune hyperparameters, and optimize models for real-world deployment.
6.    ML Pipeline: ML model deployment lifecycle tools like (MLflow)
7.    LLMs: usage of Large Language Model to simplify various tasks
8.    Research and Innovation: Stay updated with the latest NLP and machine learning research, and actively contribute to the development of state-of-the-art models and techniques.
9.    Collaboration: Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to ensure seamless integration of NLP solutions into our products.
10.   Documentation: Maintain thorough documentation of code, models, and processes for knowledge sharing and team collaboration.
 
Qualifications:
•     Bachelor's or higher degree in computer science, machine learning, artificial intelligence, or a related field.
•     Proven experience in developing NLP applications and machine learning models, with at least [4 years] years of relevant work experience.
•     Strong proficiency in programming languages such as Python and knowledge of NLP libraries and frameworks like NLTK, spaCy, Transformers, or Hugging Face.
•     Hands-on experience with deep learning frameworks such as TensorFlow or PyTorch.
•     Should have worked on at least one LLM fine tuning task
•     Strong understanding of NLP techniques, including word embeddings, attention mechanisms, and sequence-to-sequence models.
•     Excellent problem-solving skills and a data-driven approach to decision-making.
•     Strong communication skills and the ability to work in a collaborative team environment.
•     A track record of publishing research papers, contributing to open-source NLP projects, or participating in NLP competitions is a plus.