Remote, but you must be in the following location
This role is for one of the Weekday's clients
**Salary range: Rs 8000000 - Rs 14000000 (ie INR 80-140 LPA)
** Min Experience: 2 years
Location: India
JobType: full-time
Join us on a mission to revolutionize the financial industry with cutting-edge AI. As a Machine Learning Engineer , you’ll play a central role in developing advanced models that make sense of complex financial data—structured, unstructured, textual, tabular, and visual. You'll work at the intersection of machine learning, natural language processing, and computer vision to build intelligent systems that deliver real impact.
Design, develop, and deploy state-of-the-art ML models for:
Multi-modal Information Extraction : Uncover key insights from diverse data formats like text, tables, and charts.
Term Disambiguation : Identify semantically equivalent financial terms expressed in different ways.
Financial Machine Translation : Translate financial statements across languages with high fidelity.
Collaborate with software engineers, data scientists, and finance experts to scope projects and integrate models into production environments.
Build robust data pipelines for preprocessing, model training, evaluation, and deployment.
Conduct rigorous experimentation and benchmarking to ensure model accuracy and reliability.
Monitor and maintain live ML systems, proactively addressing performance issues.
Contribute to innovation by staying up to date with emerging AI/ML research and sharing knowledge across the team.
Master’s degree in Computer Science, Data Science, or related field—or equivalent industry experience.
Strong programming skills in Python and experience with Git and version control workflows.
Solid grasp of machine learning and deep learning fundamentals.
Hands-on experience with Natural Language Processing , including:
Text preprocessing, regex, tokenization, stemming, lemmatization
Transformer models and large language models (LLMs)
Familiarity with Computer Vision and basic image processing techniques.
Proficient with ML libraries and frameworks such as PyTorch, HuggingFace, OpenCV, scikit-learn, NumPy, spaCy, NLTK.
Ability to explain complex technical concepts clearly to technical and non-technical stakeholders.
Strong organizational skills and experience managing multiple projects independently.
Experience in ML research in areas like representation learning , information retrieval , or object detection.
Self-motivated with a passion for continuous learning and innovation in AI.
Experience with Django or backend development.
Exposure to LLMs , vector databases , and frameworks like LangChain.
Familiarity with deploying NLP/ML models on cloud platforms such as AWS, Azure, or GCP.
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