7 months ago
Bengaluru, IndiaSenior
Responsibilities
- Own the end-to-end design, development, deployment, and operation of production-grade AI/ML solutions.
- Build ML and NLP models, LLM-powered applications, RAG systems, and multi-agent AI systems.
- Make architectural decisions covering model selection, training strategies, retrieval mechanisms, orchestration layers, and infrastructure.
- Define evaluation metrics and implement automated evaluation, monitoring, and model quality practices.
- Implement and manage MLOps practices for reproducible pipelines, experiment tracking, deployment, and maintenance.
- Collaborate with software engineers, data scientists, and product teams to align AI capabilities with business needs.
- Mentor and coach junior AI engineers.
Requirements
- Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field.
- Hands-on experience with LLM-powered production applications or ML/NLP applications.
- Strong proficiency in Python and AI frameworks.
- Strong understanding of supervised and unsupervised learning, optimization, and model evaluation.
- Solid experience with NLP systems, including text classification, embeddings, retrieval systems, and semantic search.
- Hands-on MLOps experience with reproducible pipelines, experiment tracking, automated evaluation, monitoring, and model or AI artifact deployment.
- Experience with AI model fine-tuning, optimization, and evaluation.
- Proven experience with AWS and cloud-based AI deployments.
- Knowledge of reinforcement learning, RAG, and multi-agent AI architectures.
- Ability to inspect raw logs, design metrics, and identify quality regressions.
- Strong English communication, problem-solving, collaboration, and stakeholder communication skills.
- Preferred qualifications include scalable AI infrastructure, model latency/throughput/cost optimization, large language model fine-tuning, orchestration frameworks, and enterprise or B2B AI system design experience.
Benefits
- Permanent contract with a competitive compensation package.
- Hybrid work model balancing office and remote work, with structured onboarding for new hires.
- Health insurance including outpatient, dental, vision, health check-up, consultation, and pharmacy coverage.
- Flexible hours, unlimited paid time off, 22 additional holidays, company-paid bank holidays, sick leave, bereavement leave, and volunteer days.
- Access to professional training platforms.
- Personal accident insurance with coverage up to three times annual CTC.
- Paid maternity, paternity, and adoption leave.
- Gratuity under the Payment of Gratuity Act after at least five years of employment.
- Referral bonuses after three months of continuous employment.
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