Senior Machine Learning Engineer

About Us:

Machine Learning Studies is an innovative leader in AI and machine learning, creating cutting-edge solutions to tackle some of the most complex challenges in industries like finance, healthcare, and cybersecurity. Our expert team, composed of top talent from global tech companies, works together to revolutionize AI technologies, building scalable, enterprise-grade systems that empower our clients to stay ahead in an ever-evolving world. If you are passionate about driving AI innovation and want to be part of a high-impact, collaborative team, we want to hear from you!

Position Overview:

We are seeking an experienced Senior Machine Learning Engineer to join our growing AI team. This role offers an exciting opportunity to contribute to the design, development, and deployment of state-of-the-art machine learning models that power our transformative AI solutions. As a key member of the team, you will collaborate with data scientists, engineers, and product managers to deliver innovative solutions that solve real-world business problems.

Responsibilities:

Design & Development: Architect and implement scalable machine learning systems, including fine-tuning and optimizing large language models (LLMs) and natural language processing models (e.g., BERT, GPT) for production environments.

Model Optimization: Enhance AI models for real-time performance, ensuring high throughput, low latency, and minimal inference costs.

Cross-functional Collaboration: Work closely with product teams to identify key business challenges and translate them into effective AI/ML solutions.

Research & Innovation: Stay up-to-date with the latest advancements in AI/ML research and incorporate cutting-edge techniques into our systems.

Cloud Integration: Deploy models on cloud platforms (AWS, GCP, Azure) and leverage cloud-native technologies for scalable and cost-effective AI solutions.

Multi-Agent Systems & RaG: Develop advanced retrieval-augmented generation (RaG) systems, multi-agent architectures, and large-scale AI systems to enhance decision-making and customer value.

Quality Assurance: Ensure the quality, accuracy, and robustness of models through continuous testing, validation, and refinement.

Requirements:

Experience: 5-7+ years of professional experience in machine learning engineering with a focus on large-scale AI system design, development, and deployment.

LLM Expertise: Proven experience in working with large language models (LLMs), fine-tuning, and optimizing models such as GPT, T5, or BERT for practical use cases.

NLP & AI Frameworks: Strong expertise in NLP techniques, including text classification, named entity recognition, and question-answering. Proficiency in AI frameworks such as PyTorch, TensorFlow, Langchain, LangGraph, etc.

Programming Skills: Advanced Python programming skills with extensive experience in machine learning libraries (e.g., NumPy, SciPy, scikit-learn, Hugging Face Transformers).

Cloud & Deployment: Experience with cloud platforms (AWS, Azure, GCP) and deploying models in a cloud-based infrastructure, utilizing tools like Docker and Kubernetes.

Problem-Solving: Excellent problem-solving skills, with the ability to think critically and innovatively to solve complex technical challenges.

Communication: Strong written and verbal communication skills, with the ability to collaborate effectively across teams and with external stakeholders.

Leadership: Ability to mentor junior engineers and lead by example in developing high-quality AI systems.

Bonus Points:

Experience in deep reinforcement learning, computer vision, or advanced NLP techniques.

Familiarity with MLOps practices, including model monitoring, retraining pipelines, and version control.

What We Offer:

Competitive Compensation: (INR 24 Lakhs - 30 Lakhs per annum)

Work-Life Balance: Flexible working hours with options for remote work.

Health & Wellness Benefits: Comprehensive healthcare, wellness programs, and paid time off.

Professional Growth: Access to continuous learning opportunities, training, and a clear path for career advancement.

Collaborative Culture: A dynamic, inclusive, and supportive work environment where innovation thrives.