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
• Unite your passion for audio innovation with high-tech product development
• Create pitch-perfect, cutting-edge technology that elevates the listening experience

What You’ll Be Part Of

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.

How You’ll Make An Impact

• 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).
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What Makes You A Strong Fit 

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• 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

Things To Know

• This role is based in Bangalore, and follows a hybrid schedule, with regular in-office collaboration alongside engineering, product, and customer program teams.
• This position supports global product launch timelines, so occasional early morning or evening meetings may be needed to collaborate with teams in Europe and Asia.
• Professional working proficiency in English is required to support day-to-day communication.

What You Can Expect

• A hybrid work environment that balances flexibility with in-person collaboration, with most office-based roles onsite three days a week.
• Access to employee discounts on HARMAN and Samsung products (including JBL, Harman / Kardon, AKG, and others)
• Learning and development opportunities through our award-winning HARMAN University programs
• Wellness benefits designed to support your overall well-being
• Tuition reimbursement support
• Access to the HARMAN campus fitness center and cafeteria, where available
• An inclusive and diverse work environment that supports both your 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.