Principal Machine Learning Engineer (L5)

New

JobgetherAI customer engagement

Based in IndiaFull-TimePrincipal

Salary not disclosed

Apply NowOpens the employer's application page

Job Details

Experience: At least 10 years of applied machine learning or artificial intelligence experience
Required Skills: AWSPythonArtificial IntelligenceMachine Learning

Have at least 10 years of applied machine learning or artificial intelligence experience.
Have independently owned technically ambitious systems from conception through production deployment.
Demonstrate initiative and sound decision-making in ambiguous, early-stage product environments.
Have strong proficiency in Python and experience developing robust, maintainable software for complex ML applications.
Have a deep understanding of statistical machine learning algorithms, transformer architectures, large language models, and modern AI techniques.
Have extensive experience designing and deploying production-grade AI/ML systems, including LLM orchestration, embedding models, and vector databases.
Have hands-on experience building cloud-based services on AWS, GCP, or Microsoft Azure.
Have experience with high-volume datasets, streaming pipelines, real-time inference systems, and data storage technologies.
Be able to elevate engineering standards through mentorship, design reviews, architectural guidance, and knowledge sharing.
Have experience developing autonomous agents that manage multi-turn conversations while maintaining long-term context and consistency.
Have experience modeling user behavior, designing experiments, and applying causal or counterfactual inference methods when full randomization is not possible.
Have excellent communication skills and the ability to work effectively with multidisciplinary, geographically distributed teams.

Design, develop, and deliver machine learning capabilities for intelligent customer engagement.
Translate business and technical challenges into research initiatives, experiments, and hypothesis validation.
Implement LLM orchestration, embedding models, retrieval strategies, vector stores, and personalization techniques.
Architect, develop, and deploy scalable ML services for high-volume data, streaming, and real-time inference.
Define architectural standards and engineering practices for reliability, maintainability, performance, and scalability.
Guide engineers through technical reviews, architectural decisions, knowledge sharing, and mentoring.
Identify and integrate AI frameworks and development platforms.
Collaborate with cross-functional stakeholders to develop technical solutions and communicate research findings and trade-offs.
Apply relevant advances in machine learning, generative AI, autonomous agents, and personalization to product challenges.

View Full Description & ApplyYou'll be redirected to the employer's site