ML Engineer

Role Overview

We are looking for a passionate and skilled Machine Learning Engineer with expertise in Natural Language Processing (NLP) and a working knowledge of Computer Vision (CV). You will play a key role in developing, deploying, and optimizing state-of-the-art AI/ML models to power intelligent solutions that impact millions of users.

Key Responsibilities

• Design, develop, and deploy NLP solutions for tasks such as text classification, information extraction, language modeling, and conversational AI.
• Work on Computer Vision projects involving image classification, object detection, and other related tasks.
• Collaborate with data engineers to preprocess and curate large datasets for training and testing models.
• Experiment with state-of-the-art machine learning algorithms and fine-tune models for production.
• Build and deploy scalable, production-ready machine learning pipelines.
• Analyze and optimize the performance of ML models to meet business requirements.
• Stay updated with the latest advancements in NLP and CV and propose innovative solutions to enhance products.

Required Skills and Qualifications

• Education: Bachelors or Masters degree or PhD. in Computer Science, Data Science, or a related field.
• Experience: 3 to 6 years of professional experience in building ML models with a focus on NLP.
• Technical Skills:
• Expertise in NLP tasks and frameworks (e.g., transformers, Hugging Face, SpaCy, NLTK, or similar).
• Experience in developing and fine-tuning deep learning models using TensorFlow or PyTorch.
• Proficiency in Python and libraries such as NumPy, pandas, and scikit-learn.
• Exposure to Computer Vision frameworks like OpenCV, YOLO, or torchvision.
• Familiarity with pre-trained models for NLP (e.g., BERT, GPT, T5) and CV (e.g., ResNet, EfficientNet).
• Knowledge of cloud platforms (AWS, Azure, or GCP) for deploying ML models.
• Strong understanding of ML lifecycle tools (e.g., MLflow, DVC, or similar).
• Experience with distributed computing and handling large datasets is a plus.

Soft Skills:

• Strong problem-solving abilities and analytical mindset.
• Excellent communication skills to convey complex ideas effectively.
• Ability to work collaboratively in a team-oriented environment.

Preferred Qualifications

• Experience with large language models (LLMs) and fine-tuning for domain-specific tasks.
• Exposure to multimodal learning (integrating NLP and CV models).
• Knowledge of MLOps practices, including containerization and CI/CD pipelines.
• Familiarity with GANs, autoencoders, or other advanced ML techniques.
• Publications or contributions to open-source projects in NLP or CV domains.

What We Offer

• Competitive salary and performance bonuses.
• Opportunity to work on exciting, cutting-edge projects.
• Flexible working hours and a collaborative environment.
• Professional growth opportunities through training and mentorship.
• Health insurance, Learning budgets, etc.
• MacBook for effective work and productivity
• Disconnect Week during Christmas to new year