Senior ML Engineer

8 years

0 Lacs

Posted:2 days ago| Platform: Linkedin logo

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Job Description

🧠 Job Title: Senior Machine Learning Engineer

Company

Location

Type

Experience

Education

🚀 About Darwix AI

Darwix AI

Transform+

Senior Machine Learning Engineer

🎯 Role Overview

high-impact, high-ownership role

Your work will directly power critical product features: from personalized agent nudges and conversation scoring to lead scoring, smart recommendations, and retrieval-augmented generation (RAG) pipelines.

You’ll be the bridge between data science, engineering, and product — converting ideas into models, and models into production-scale systems with tangible business value.

🧪 Key Responsibilities🔬 1. Model Design, Training, and Optimization
  • Develop and fine-tune machine learning models using structured, unstructured, and semi-structured data sources.
  • Work with models across domains: text classification, speech transcription, named entity recognition, topic modeling, summarization, time series, and recommendation systems.
  • Explore and implement transformer architectures, BERT-style encoders, Siamese networks, and retrieval-based models.
📊 2. Data Engineering & Feature Extraction
  • Build robust ETL pipelines to clean, label, and enrich data for supervised and unsupervised learning tasks.
  • Work with multimodal inputs — audio, text, metadata — and build smart representations for downstream tasks.
  • Automate data collection from APIs, CRMs, sales transcripts, and call logs.
⚙️ 3. Productionizing ML Pipelines
  • Package and deploy models in scalable APIs (using FastAPI, Flask, or similar frameworks).
  • Work closely with DevOps to containerize and orchestrate ML workflows using Docker, Kubernetes, or CI/CD pipelines.
  • Ensure production readiness: logging, monitoring, rollback, and fail-safes.
📈 4. Experimentation & Evaluation
  • Design rigorous experiments using A/B tests, offline metrics, and post-deployment feedback loops.
  • Continuously optimize model performance (latency, accuracy, precision-recall trade-offs).
  • Implement drift detection and re-training pipelines for models in production.
🔁 5. Collaboration with Product & Engineering
  • Translate business problems into ML problems and align modeling goals with user outcomes.
  • Partner with product managers, AI researchers, data annotators, and frontend/backend engineers to build and launch features.
  • Contribute to the product roadmap with ML-driven ideas and prototypes.
🛠️ 6. Innovation & Technical Leadership
  • Evaluate open-source and proprietary LLM APIs, AutoML frameworks, vector databases, and model inference techniques.
  • Drive innovation in voice-to-insight systems (ASR + Diarization + NLP).
  • Mentor junior engineers and contribute to best practices in ML development and deployment.
🧰 Tech Stack🔧 Languages & Frameworks
  • Python (core), SQL, Bash
  • PyTorch, TensorFlow, HuggingFace, scikit-learn, XGBoost, LightGBM
🧠 ML & AI Ecosystem
  • Transformers, RNNs, CNNs, CRFs
  • BERT, RoBERTa, GPT-style models
  • OpenAI API, Cohere, LLaMA, Mistral, Anthropic Claude
  • FAISS, Pinecone, Qdrant, LlamaIndex
☁️ Deployment & Infrastructure
  • Docker, Kubernetes, GitHub Actions, Jenkins
  • AWS (EC2, Lambda, S3, SageMaker), GCP, Azure
  • Redis, PostgreSQL, MongoDB
📊 Monitoring & Experimentation
  • MLflow, Weights & Biases, TensorBoard, Prometheus, Grafana
👨‍💼 Qualifications🎓 Education
  • Bachelor’s or Master’s degree in CS, AI, Statistics, or related quantitative disciplines.
  • Certifications in advanced ML, data science, or AI are a plus.
🧑‍💻 Experience
  • 4–8 years of hands-on experience in applied machine learning.
  • Demonstrated success in deploying models to production at scale.
  • Deep familiarity with transformer-based architectures and model evaluation.
✅ You’ll Excel In This Role If You…
  • Thrive on solving end-to-end ML problems — not just notebooks, but deployment, testing, and iteration.
  • Obsess over clean, maintainable, reusable code and pipelines.
  • Think from first principles and challenge model assumptions when they don’t work.
  • Are deeply curious and have built multiple projects just because you wanted to know how something works.
  • Are comfortable working with ambiguity, fast timelines, and real-time data challenges.
  • Want to build AI products that

    get used by real people

    and

    drive revenue outcomes

    — not just vanity demos.
💼 What You’ll Get at Darwix AI
  • Work with some of the

    brightest minds in AI

    , product, and design.
  • Solve AI problems that push the boundaries of real-time, voice-first, multilingual enterprise use cases.
  • Direct mentorship from senior architects and AI scientists.
  • Competitive compensation (₹30L–₹45L CTC) + ESOPs + rapid growth trajectory.
  • Opportunity to shape the future of a

    global-first AI startup

    built from India.
  • Hands-on experience with the most advanced tech stack in applied ML and production AI.
  • Front-row seat to a generational company that is redefining enterprise AI.
📩 How to Apply

Ready to build with us?

Send your resume, GitHub/portfolio, and a short write-up on:

“What’s the most interesting ML system you’ve built — and what made it work?”

people@darwix.ai

Senior ML Engineer – Application

🔐 Final Notes

We value speed, honesty, and humility. We ship fast, fail fast, and learn even faster. This role is designed for high-agency, hands-on ML engineers who want to make a difference — not just write code.

own real impact

Darwix AI – GenAI for Revenue Teams. Built from India, for the World.

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