Principal, Machine Learning Engineer (L5)

Jobgether SRL; United States; Remote; USD 180,000 - 260,000; Full time

Benefits offered by this job

Remote-first working arrangements

Healthcare benefits

Paid time off

Parental leave

Retirement savings

Professional growth

Travel opportunities

Job summary

Jobgether SRL is seeking a senior AI/ML leader to drive innovative machine learning capabilities for intelligent customer engagement. You will translate ambiguous challenges into structured research programs, design experiments, and push state-of-the-art LLM orchestration and contextual intelligence into production-scale services.

The role demands deep expertise in transformer models, embeddings, vector stores, and data-driven personalization, with hands-on cloud experience and a track record of

Qualifications

• : At least 10 years of applied machine learning or AI experience with ownership of end-to-end systems.
• : Demonstrated ability to operate in ambiguous, early-stage product environments.
• : Strong Python software-development experience for complex ML applications.
• : Deep understanding of ML algorithms, transformers, LLMs, and modern AI techniques.
• : Experience designing production-grade AI/ML systems including LLM orchestration and embeddings.
• : Hands-on experience building cloud-based services on AWS, GCP, or Azure.
• : Experience with high-volume data, streaming pipelines, and real-time inference.
• : Ability to mentor engineers and influence engineering standards.
• : Excellent communication and collaboration skills across distributed teams.
• : Preferred: experience with autonomous agents and long-term context management.

Responsibilities

• Lead AI/ML innovation: design, develop, and deliver advanced machine learning capabilities.
• Drive research and experimentation: translate business challenges into structured research initiatives; design experiments; validate hypotheses.
• Advance LLM & contextual intelligence: implement state-of-the-art LLM orchestration, embeddings, vector stores, personalization.
• Build production-grade ML systems: architect and deploy scalable ML services for high-volume data and real-time inference.
• Establish technical excellence: set architectural standards, practices, and design principles for reliability and scalability.
• Provide technical leadership and mentorship: guide engineers through reviews, decisions, and knowledge sharing.
• Leverage modern AI development tools: integrate new frameworks to speed delivery and reduce repetitive work.
• Collaborate across teams: translate complex requirements and share findings with stakeholders.
• Continuously evolve technical expertise: stay current on generative AI advances and apply them to the product challenges.

Skills

AI/ML Innovation

Research & Experimentation

LLM Orchestration

Production ML Systems

Technical Leadership

Modern AI Tools

Cross-functional Collaboration

Continuous Learning

Distributed Teams

Education

10+ years ML/AI experience

Tools

Python

TensorFlow / PyTorch

Cloud (AWS/GCP/Azure)

Vector Stores / Embeddings

LLM Platforms

Job description

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.