Advanced Engineer: ML, LLM, NLP, RAG

Introduction: A Career at HARMAN Automotive

We’re a global, multi-disciplinary team that’s putting the innovative power of technology to work and transforming tomorrow. At HARMAN Automotive, we give you the keys to fast-track your career.

• Engineer audio systems and integrated technology platforms that augment the driving experience
• Combine ingenuity, in-depth research, and a spirit of collaboration with design and engineering excellence
• Advance in-vehicle infotainment, safety, efficiency, and enjoyment

About the Role

As an AI Technical Lead, you will own end-to-end delivery of production-grade AI systems, including LLM-powered applications, RAG pipelines, NLP solutions, and multimodal models involving audio and images. You will integrate these capabilities into engineering workflows to improve quality, speed, and traceability across the Car Audio development lifecycle.

This role is ideal for an engineer with strong implementation + SDLC exposure, who can guide architecture over time and lead a small team to deliver real, measurable outcomes.

What You Will Do

• Lead development of AI tools that improve productivity and quality across:
  • Systems Engineering: requirements parsing, ambiguity detection, traceability automation, change impact analysis
  • Software Engineering: code intelligence, defect/risk prediction, review assistants, documentation automation
  • Testing & Validation: test case generation, log/trace analytics, failure clustering, intelligent triage, coverage optimization
• Drive tool adoption via measurable improvements (cycle time reduction, faster triage, improved quality metrics).

NLP, LLMs & RAG Applications

• Develop and fine-tune transformer-based models (BERT/GPT-class, etc.) for classification, similarity, and automation.
• Build Retrieval-Augmented Generation (RAG) pipelines using vector databases (FAISS, Pinecone, etc.).
• Implement prompt engineering, evaluation, and guardrails (privacy, safety, hallucination control).
• Build copilots/assistants for engineering teams (Systems/SW/Test) with strong reliability and auditability.

Deployment, MLOps & SDLC Integration

• Containerize AI services using Docker and support deployment on Kubernetes and/or cloud (AWS/Azure/GCP).
• Establish MLOps practices: experiment tracking, model registry/versioning, CI/CD for ML, monitoring, drift detection.
• Implement observability for AI tools (latency, failures, data drift, usage analytics); Prometheus/Grafana exposure is a plus.

Team Leadership

• Lead and mentor a team of ~5 engineers: planning, technical execution, code reviews, and delivery ownership.
• Coordinate with global stakeholders, manage priorities, and ensure predictable execution.
• Enforce engineering best practices (secure coding, testing, documentation, maintainability).

What You Need to Be Successful

• 8+ years of hands-on experience in AI/ML engineering with production deployments.
• Strong exposure to SDLC in large-scale product environments.
• Proven experience delivering AI-enabled tooling or platforms used by engineers.
• Bachelor’s/Master’s in CS/AI/Data Science or related field.
• Automotive/embedded exposure is a plus (Car Audio domain strongly preferred).
• Python (Advanced)
• PyTorch / TensorFlow
• NLP/LLMs: HuggingFace Transformers, orchestration frameworks, prompt engineering
• RAG + vector databases (FAISS/Pinecone/etc.)
• Multimodal ML:
  • Audio processing libraries (e.g., librosa/torchaudio) and feature pipelines (e.g., mel-spectrograms)
  • Image processing / vision models (OpenCV, CNN/ViT-based approaches)
  • Multimodal embeddings and retrieval (audio/image/text)
• Docker, Git, Linux
• Cloud exposure (AWS/Azure/GCP), Kubernetes familiarity
• CI/CD fundamentals and monitoring/observability basics

Bonus Points if You Have

• Experience with audio ML in automotive (acoustic tuning/QoE, in-cabin signals, infotainment-related audio analytics)
• Multimodal LLM or VLM exposure (image+text understanding, document AI, multimodal RAG)
• Inference optimization (quantization, batching, GPU acceleration)
• MLOps tooling (MLflow or similar)
• Knowledge of ASPICE / ISO 26262 concepts, traceability, verification evidence automation

What Makes You Eligible

• Occasional travel (if required)
• Willingness to work from HARMAN office in Bengaluru (Hybrid model).
• Successful completion of background verification

What We Offer

• Flexible work environment, allowing for full-time remote work globally for positions that can be performed outside a HARMAN or customer location.
• Access to employee discounts on world-class products (JBL, HARMAN Kardon, AKG, and more)
• Extensive training opportunities through our own HARMAN University
• Competitive wellness benefits
• Tuition reimbursement
• “Be Brilliant” employee recognition and rewards program.
• An inclusive and diverse work environment that fosters and encourages professional and personal development.

#LI-AR2

HARMAN is proud to be an Equal Opportunity / Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.