Senior AI/ML Engineer

We're seeking an experienced AI/ML Engineer to research, customize, and deploy machine learning models across audio, vision, and language domains. You'll work on production systems that process multimodal data at scale and build automation solutions for our data platform serving global AI/ML customers. The ideal candidate brings 10+ years of overall software engineering experience, including 6+ years of hands-on

Python

development 6+ years of Machine Learning experience with deep expertise in

Conversational AI /Speech Processing and/or

Computer Vision 2+ years working with

Large Language Models

(LLM) and

Generative AI

applications 3+ years of experience mentoring engineers or leading technical initiatives

Key Responsibilities Research, evaluate, and customize open-source ML models (audio, vision, LLM) for production use cases on AWS Develop APIs and services using FastAPI, Django, or similar frameworks to expose ML capabilities Design automation solutions and scripts for data processing, validation, and quality control across multimodal datasets (audio, image, video, text) Build and maintain MLOps pipelines for model versioning, deployment, monitoring, continuous integration, and performance optimization Provide technical leadership on ML architecture decisions, model selection, and system design trade-offs Drive technical initiatives from concept to production, including feasibility analysis, prototyping, and deployment strategy Mentor junior ML engineers through code reviews, technical guidance, and knowledge sharing Collaborate with cross-functional teams to translate research outcomes into scalable, production-ready systems

Qualifications & Experience: Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field Proven expertise in Python with strong foundation in object-oriented programming and design patterns Experience with Python frameworks: FastAPI, Django, Celery, Streamlit Proficiency with ML/DL frameworks: TensorFlow, PyTorch, Keras, Scikit-learn Experience building and consuming RESTful APIs in production environments Solid understanding of system design and architecture principles, along with MLOps practices and tools for versioning, evaluation, deployment, observability Experience developing scripts for data pipeline management and workflow automation Familiarity with cloud-based environments (AWS/GCP/Azure) and testing strategies for production ML systems to ensure model accuracy, performance, and reliability Experience processing and analyzing large-scale unstructured multimodal data Hands-on experience developing and deploying

Generative AI/LLM

applications with expertise in LangChain, LangGraph, vector databases, RAG systems, prompt engineering, model optimization, and LLM evaluation using open-source frameworks and tools Hands-on experience customizing and optimizing open-source ML models, with expertise in at least one of the following domains: Speech/Audio

Processing

tasks such as Voice Activity Detection, Speaker Diarization, Speaker Embeddings, Automatic Speech Recognition (ASR), audio classification etc Computer Vision

tasks such as Object detection, face recognition, image classification, video analysis Excellent communication skills with ability to explain complex technical concepts to both technical and non-technical stakeholders Proven ability to mentor junior ML engineers, lead technical initiatives, and work independently in dynamic, cross-functional environments