About Docsumo: Docsumo is your go-to Document AI solution for streamlining business operations. We turn complex documents like bank statements, policies, and financial statements into valuable, actionable data. Our cutting-edge technology helps businesses make smarter decisions faster. We are backed by marquee investors such as Sequoia, Barclays, Fifth Wall, Common Ocean, and Techstars. At Docsumo, we're on a mission to revolutionize how businesses handle data. We empower companies to: Boost efficiency by 6-10 times Make quick, accurate decisions from unstructured information Scale operations effortlessly through innovative technology The opportunity as Senior Machine Learning Engineer:

We are seeking senior professionals with over 4 years of experience in the field. This is a role for candidates with a proven track record in machine learning, deep learning, NLP, and computer vision. 

If you have led and managed a team of ML scientists and engineers and have a strong foundation in deploying end-to-end ML solutions, this opportunity is for you.

This role offers the chance to rapidly advance into leadership positions, such as Lead ML Engineer, where you'll spearhead critical projects with creative autonomy.

You'll work closely with our CTO, Data Science, and Engineering teams, shaping the future of intelligent document processing for our expanding client base in the US.

This is a full-time role with flexible options, including hybrid work in Kathmandu or remote work from India.

Working hours are 10:00 am to 7:00 pm IST, with a 1-hour lunch break.

You will report directly to the Data Science Lead or the CTO, collaborating with a talented team to deliver innovative ML solutions that drive customer success.

Key Responsibilities

Collaborate with cross-functional teams of scientists and engineers to design, develop, and implement advanced machine learning systems that transform innovative ideas from conceptual stages into operational APIs.

Conduct cutting-edge research in machine learning, focusing on the application and fine-tuning of Large Language Models (LLMs) to develop robust, scalable solutions for intelligent document processing.

Lead a team of data scientists and machine learning engineers, providing mentorship and fostering a culture of collaboration and continuous learning to achieve high performance and innovative outcomes.

Plan, manage, and oversee the full lifecycle of ML projects, ensuring alignment with business goals and timely delivery of high-quality solutions. Develop and apply sophisticated machine learning algorithms to address complex business challenges, particularly those involving the processing and analysis of unstructured data.

Engage in Agile development processes including regular standups, sprint planning, and retrospectives to facilitate iterative progress and maintain high standards of output.

Ensure the documentation of machine learning methodologies, model development processes, and maintain rigorous testing standards to ensure reliability and efficiency of models in production.

Drive the integration and optimization of LLMs and other advanced models to enhance performance and operational efficiency, continuously seeking improvements.

Need to Have:

At least 4 years of industry experience in machine learning, deep learning, NLP, and computer vision, ideally within tech companies, product startups, or R&D environments.

1-2 years of experience leading teams of 4-5+ ML scientists and engineers, demonstrating effective leadership and project management skills. Proficiency in PyTorch and TensorFlow, with experience in training deep neural networks, implementing transfer learning, and optimizing models.

Strong skills in classification and regression techniques, with hands-on experience in Scikit-learn, Numpy, Pandas, and Scipy. Practical experience with Transformers, such as BERT and GPT, for tasks like text classification, entity recognition, and sentiment analysis.

Proficiency in Python and strong understanding of Object-Oriented Programming (OOP) principles.

Experience with version control using Git, cloud platforms like AWS and Google Cloud, and containerization technologies such as Docker and Kubernetes.

Ability to work effectively in a team, demonstrating motivation, resourcefulness, and a growth mindset.

Bachelor’s degree in Computer Science, Statistics, Machine Learning, Physics, Mathematics, or a related field.

Nice to Have:

Experience with Large Language Models, including techniques like PEFT, prompt engineering, few-shot learning, and RLHF.

Knowledge of computer vision applications like OCR, OpenCV, CNNs, and multimodal AI.

Experience with advanced data visualization libraries.

Familiarity with Agile development practices and sprint management.

A track record of innovative research contributions or publications in the machine learning domain.