Lead Data Scientist - Autonomous Goal Management

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Lead Data Scientist - Autonomous Goal Management in the United States.

In this role, you will lead the development of advanced AI agents capable of autonomously setting, adapting, and achieving complex goals in dynamic environments. You will design and implement intelligent systems that combine planning, reasoning, and feedback integration to enable safe and efficient long-horizon decision-making. The position requires bridging research and production execution, ensuring agents operate reliably and robustly while aligning with human intent. You will mentor a team of data scientists, collaborate across engineering and product teams, and establish evaluation metrics to assess agent performance and safety. This role offers a challenging, innovative, and collaborative environment focused on pushing the boundaries of autonomous AI systems.

Accountabilities:

• Architect goal-setting and decomposition mechanisms for autonomous agents in uncertain or open-ended environments.
• Design and implement dynamic planning systems, including hierarchical planning, curriculum learning, and self-refinement loops.
• Develop memory, tool-use, and feedback-loop frameworks to enable multi-step, self-directed agent behavior.
• Create evaluation frameworks to measure alignment with human intent, consistency, and progress against long-horizon objectives.
• Prototype agents interfacing with APIs, servers, search engines, databases, or real-world actuators to pursue goals safely and efficiently.
• Identify and mitigate goal misalignment, looping behaviors, and undesirable emergent strategies.
• Collaborate with cross-functional teams to integrate goal alignment with safety, reliability, and operational protocols.

• Master’s Degree with 4+ years of experience in research, ML engineering, or applied research focused on production-ready AI solutions.
• 2+ years of experience leading AI/ML system development.
• Expertise in autonomous agent design, planning, and control in dynamic environments.
• Proficiency in Python, SQL, and data analysis/data mining tools.
• Experience with ML frameworks such as PyTorch, JAX, LangChain, LangGraph, or AutoGen.
• Experience with high-performance, large-scale ML systems and language modeling with transformers.
• Knowledge of symbolic planning, causal reasoning, and model-based reinforcement learning.
• Experience with large-scale ETL pipelines.
• Preferred: Ph.D. in Computer Science, Data Science, Machine Learning, or a related field.
• Preferred: Experience deploying autonomous or semi-autonomous agents in production or simulation.
• Preferred: Familiarity with LLM-based agents using scratchpad/self-reflection or hierarchical task decomposition.
• Preferred: Understanding of autonomy risk mitigation strategies, including off-switch protocols and bounded rationality.

• Competitive base salary: $142,300 – $195,700 USD per year, plus performance-based bonuses.
• Comprehensive health, dental, and vision insurance starting day one.
• Generous paid time off, company holidays, and volunteer leave.
• Paid parental and caregiver leave.
• 401(k) retirement plan with excellent company match.
• Flexible remote work options and home office support.
• Well-being programs and professional development opportunities.

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 3 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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