Design and implement machine learning models, lead initiatives from concept to operation, and collaborate with geographically distributed teams. Key requirements include experience with LLMs, foundational models, and related research. Strong analytical and problem-solving skills are essential.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Role - Senior Machine Learning Engineer
Experience - 5+Yrs
Location - Remote
Minimum Qualifications
● Bachelor’s or Master’s degree in Science or Engineering with strong programming, data science, critical thinking, and analytical skills
● 5+ years of experience building in ML and Data science
● Recent demonstrable hand-on experience with LLMs - integrating off-the-shelf LLM’s, fine-tuning smaller models, building RAG pipelines, designing agentic flows, and other optimization techniques with LLMs
● Strong conceptual understanding of foundational models, transformers, and
related research
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● Strong conceptual understanding of the basics of machine learning and deep learning with expertise in Computer Vision and Natural Language Processing
● Recent demonstrable experience with managing large datasets for AI projects
● Experience with implementing AI projects in Python and working knowledge of associated Python libraries - numpy, scipy, pandas, sklearn, matplotlib, nltk, etc.
● Experience with Hugging Face, Spacy, BERT, Tensorflow, Torch, OpenRouter, Modal, and similar services / frameworks
● Ability to write clean, efficient, and bug-free code.
● Proven ability to lead initiatives from concept to operation while navigating challenges effectively.
● Strong analytical and problem-solving skills
● Excellent communication and interpersonal skills
Preferred Qualifications
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● Recent experience with implementing state-of-the-art scalable AI pipelines for extracting data from unstructured / semi-structured sources and converting it into structured information, along with necessary technical infrastructure to support
deployment
● Experience with cloud platforms (AWS, GCP, Azure), containerization (Kubernetes, ECS, etc.), and managed services like Bedrock, SageMaker, etc.
● Experience with MLOps practices, e.g. model monitoring, feedback pipelines, CI/CD flows, and governance best-practices
● Experience working with applications hosted on AWS or Django web frameworks.
● Familiarity with databases and web application architecture.
● Experience working with OCR tools or PDF processing libraries.
● Completed academic or online specializations in Machine Learning or Deep Learning.
● Track record of publishing research in top-tier conferences and journals
● Participation in competitive programming (e.g., Kaggle competitions) or contributions to open-source projects.
● Experience working with geographically distributed teams across multiple time zones.
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