Principal, Machine Learning Engineer (L5)

Lever, Inc.; India; Remote; INR 400,000 - 700,000; Full time

Benefits offered by this job

Remote-first

Generous PTO

Parental leave

Healthcare benefits

Retirement savings program

Travel opportunities

Job summary

Lever, Inc. in India is seeking a Principal Machine Learning Engineer to lead the next generation of AI-powered customer engagement solutions. You will design scalable ML systems, steer LLM orchestration, embeddings, and retrieval strategies, and mentor engineers across global teams.

You will translate complex business needs into disciplined experiments, drive rapid delivery, and establish architectural standards that improve reliability, performance, and personalization at scale.

Qualifications

• At least 10 years of applied ML/AI experience with ownership of production systems.
• Ability to operate in ambiguous, early-stage product environments and deliver.
• Strong Python and software engineering practices for ML apps.
• Deep knowledge of transformers, LLMs, and modern AI techniques.
• Experience deploying production-grade ML systems with LLM orchestration.
• Hands-on cloud experience (AWS/GCP/Azure).
• Data-intensive systems, streaming pipelines, real-time inference.
• Strong communication, leadership, and cross-functional collaboration.

Responsibilities

• Lead AI/ML innovation for intelligent customer engagement.
• Translate business challenges into rigorous research and experiments.
• Advance LLM and contextual intelligence capabilities with state-of-the-art methods.
• Build and deploy scalable ML services for high-volume data and real-time workloads.
• Define standards, best practices, and architectural design principles.
• Provide technical leadership and mentorship across teams.
• Integrate emerging AI frameworks to speed up implementation.
• Collaborate with cross-functional stakeholders to translate requirements.
• Stay updated on advances in ML, generative AI, and personalization.

Skills

Python

Technical leadership

Communication

Experimentation

Mentoring

Tools

LLM Orchestration

Vector Databases

Embedding Models

Cloud Platforms (AWS/GCP/Azure)

Real-time Inference

Job description

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Principal, Machine Learning Engineer (L5) based in India.

We are seeking a highly experienced Principal Machine Learning Engineer to build the next generation of AI-powered customer engagement solutions. In this role, you will develop foundational machine learning capabilities that enable applications, AI agents, and communication channels to understand customer context, behavior, and preferences. You will lead the design and implementation of advanced AI/ML systems, bridging cutting-edge research with scalable, production-ready engineering. Working on complex challenges involving large language models (LLMs), retrieval strategies, and personalized experiences, you will transform innovative ideas into impactful solutions. You will operate in a fast-paced, remote-first environment that values experimentation, technical excellence, and rapid delivery. This is an opportunity to influence technical direction, mentor engineering talent, and shape intelligent customer experiences at global scale.

Accountabilities

• Lead AI/ML innovation: Design, develop, and deliver advanced machine learning capabilities for intelligent customer engagement, supporting new functionality within a rapidly evolving product environment.
• Drive research and experimentation: Translate ambiguous business and technical challenges into structured research initiatives, design rigorous experiments, and validate hypotheses through rapid development cycles.
• Advance LLM and contextual intelligence capabilities: Investigate and implement state-of-the-art LLM orchestration, embedding models, retrieval strategies, vector stores, and data-driven personalization techniques.
• Build production-grade ML systems: Architect, develop, and deploy scalable machine learning services capable of processing high-volume data and supporting streaming and real-time inference workloads.
• Establish technical excellence: Define architectural standards, engineering best practices, and design principles that improve system reliability, maintainability, performance, and scalability.
• Provide technical leadership and mentorship: Guide engineers through technical reviews, architectural decisions, knowledge sharing, and mentoring, raising the team's capabilities without requiring formal management authority.
• Leverage modern AI development tools: Identify and integrate emerging AI frameworks and development platforms to accelerate implementation, reduce repetitive engineering work, and focus resources on high-value innovation.
• Collaborate across teams: Work closely with cross-functional stakeholders to translate complex requirements into effective technical solutions and communicate research findings, trade-offs, and implementation strategies.
• Continuously evolve technical expertise: Stay informed about advances in machine learning, generative AI, autonomous agents, and personalization, applying relevant developments to real-world product challenges.

Requirements

• Professional experience: At least 10 years of applied machine learning or artificial intelligence experience, with a proven track record of independently owning technically ambitious systems from conception through production deployment.
• Technical leadership: Demonstrated ability to operate in ambiguous, early-stage product environments, take initiative, make informed decisions, and deliver results without waiting for fully defined requirements.
• Programming expertise: Strong proficiency in Python and experience developing robust, maintainable software for complex machine learning applications.
• Machine learning foundations: Deep understanding of statistical machine learning algorithms, transformer architectures, large language models, and modern AI techniques.
• Production AI/ML architecture: Extensive experience designing, architecting, and deploying production-grade AI/ML systems, including LLM orchestration, embedding models, and vector databases.
• Cloud engineering: Hands‑on experience building cloud‑based services on AWS, Google Cloud Platform (GCP), or Microsoft Azure.
• Data‑intensive systems: Experience working with high‑volume datasets, streaming pipelines, real‑time inference systems, and diverse data storage technologies.
• Technical influence: Ability to elevate engineering standards through mentorship, design reviews, architectural guidance, and effective knowledge sharing.
• Communication and collaboration: Excellent communication skills, sound technical judgment, and the ability to work effectively with multidisciplinary and geographically distributed teams.
• Preferred experience: Previous work developing autonomous agents capable of managing multi‑turn conversations while maintaining long‑term context and consistency.
• Predictive modeling expertise: Experience modeling user behavior, designing experiments, and applying causal or counterfactual inference methods when full randomization is not possible.
• Global collaboration: Experience working within distributed teams across different locations and time zones.

Benefits

• Competitive compensation aligned with experience, skills, and local market conditions.
• Remote‑first working arrangements for eligible employees based in India.
• Generous paid time off to support rest, personal commitments, and work‑life balance.
• Parental leave and additional wellness leave.
• Healthcare benefits, with specific offerings depending on location.
• Retirement savings programs, subject to local eligibility and plan availability.
• Opportunities to work on advanced AI/ML technologies and solve complex, large‑scale engineering challenges.
• A collaborative, globally distributed environment that encourages innovation, continuous learning, and professional growth.
• Opportunities to influence technical strategy, mentor talented engineers, and contribute to high‑impact AI‑powered products.
• Support for employee volunteering and charitable giving initiatives.
• Occasional travel for team gatherings, customer meetings, and in‑person collaboration may be required.

We appreciate your interest and wish you the best!

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