Machine Learning Engineer - job 1 of 2

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Machine Learning Engineer in the United States.

As a Machine Learning Engineer, you will play a pivotal role in building advanced AI systems that process and reason over complex, high-volume log data. You will design and implement intelligent agentic components, optimize data pipelines, and develop innovative approaches to AI observability and model interpretability. Working in a small, high-impact team, you will collaborate with product, infrastructure, and data teams to deliver real-time, actionable insights. This position offers the opportunity to work with cutting-edge LLM infrastructure, shape emerging AI practices, and directly impact the development of autonomous AI agents. The environment is fast-paced, collaborative, and focused on experimentation, learning, and delivering measurable outcomes.

• Accountabilities:
• Design, implement, and optimize agentic AI components, including memory management, context engineering, and prompt strategies.
• Develop and maintain high-quality datasets, ensuring representativeness and reliability for model training and evaluation.
• Prototype and evaluate novel prompting strategies, reasoning chains, and model interpretability techniques.
• Collaborate cross-functionally with product, data, and infrastructure teams to deliver end-to-end AI-powered insights.
• Operate autonomously in a fast-paced, ambiguous environment, defining scope, setting milestones, and driving outcomes.
• Ensure reliability, performance, and observability of deployed AI agents through rigorous testing and continuous improvement.
• Deliver incremental improvements that directly enhance the quality and utility of AI-powered systems.
• Requirements:
• B.Tech, M.Tech, or Ph.D. in Computer Science, Data Science, or a related field.
• 1–2 years of hands-on industry experience with demonstrable ownership and delivery.
• Strong understanding of machine learning fundamentals, data pipelines, and model evaluation.
• Proficiency in Python and ML/data libraries (NumPy, pandas, scikit-learn); familiarity with JVM languages is a plus.
• Working knowledge of LLM core concepts, agentic AI design patterns, and prompt engineering.
• Strong collaboration and communication skills with a passion for shaping emerging AI paradigms.
• Ability to work effectively in an autonomous, fast-paced, and experimental environment.
• Desired Qualifications:
• Experience deploying AI agents or LLM applications in production.
• Familiarity with agentic AI frameworks (e.g., LangChain, LangGraph, CrewAI).
• Experience with ML infrastructure and tooling (PyTorch, MLflow, Airflow, Docker, AWS).
• Knowledge of LLM Ops, including infrastructure optimization, observability, latency, and cost monitoring.
• Located in the Pacific Time zone preferred.
• Benefits:
• Competitive salary range: $148,000–$173,200 USD, plus bonus and equity opportunities.
• Comprehensive health, dental, and vision insurance.
• Retirement savings plan eligibility.
• Paid time off and flexible work arrangements.
• Remote-first work environment with opportunities for collaboration across teams.
• Access to cutting-edge AI tools and resources to support professional growth and learning.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.

🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.

📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.

🎯 Based on this analysis, we automatically shortlist the three candidates with the highest match to the role.

🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

Thank you for your interest!

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