Staff Machine Learning Engineer - Agentic Models, LLM, RAG, GenAI

Anywhere Real Estate • $232K — $310K *
Enterprise Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Passion for machine learning, generative AI, large language models (LLMs), and natural language processing (NLP).
  • Solid foundation in agent-based modeling, reinforcement learning, and autonomous systems.
  • Hands-on experience with building and deploying LLMs in Agentic AI applications.
  • Proficient in Python and familiar with frameworks such as TensorFlow or PyTorch.
  • Experience with cloud services like AWS and container tools including Docker and Kubernetes.
  • Knowledge of distributed system patterns and microservices architecture.
  • Experience with message queuing systems like AWS SQS and Apache Kafka.
  • Hands-on experience with API design and system integration.
  • Strong analytical skills with a problem-solving mindset.
  • Excellent communication and teamwork abilities.
  • Master's/Ph.D. in Computer Science, AI, or related fields, or equivalent experience.
  • 6-10+ years of relevant AI and machine learning industry experience.
  • Proven ability to advance systems from prototype to production.
  • Experience with RAG architectures and vector databases.
  • Familiarity with multi-agent workflow frameworks like LangGraph.

Responsibilities

  • Lead research, design, development, and deployment of advanced AI agents and systems.
  • Architect and implement complex multi-agent systems focused on planning and execution.
  • Develop and integrate LLMs to enhance autonomy and intelligent capabilities of agents.
  • Build scalable and reliable infrastructure for AI agent deployment.
  • Diagnose and optimize performance issues in distributed environments.
  • Facilitate team knowledge sharing and technical growth.
  • Stay informed on advancements in AI research relevant to Agentic AI.
  • Utilize enterprise and market data to enhance agent experiences.

Benefits

  • Comprehensive family medical, vision, and dental coverage.
  • Eligibility for equity awards and discretionary bonuses.
  • Flexible hybrid work environment to promote collaboration.
  • Focus on employee wellbeing and dynamic working conditions.
Full Job Description
Staff Machine Learning Engineer - Agentic Models, LLM, RAG, GenAI

About AII/ML Team

Our AI/ML team is building the core technology that makes our platform autonomous and agentic. This team is the driving force behind Eightfold's cutting-edge solutions. We're a group of passionate experts who thrive on pushing the boundaries of applied machine learning. We work with massive datasets, tackle complex challenges, and focus on real-world reliability, shipping systems that manage multi-step reasoning and distributed state management at enterprise scale.

You will work with enormous data sets to build intelligent agents that proactively assist millions of users across 100+ countries and 30+ different languages.

Responsibilities:
  • Lead the team in: research, design, development, and deployment of advanced AI agents and agentic systems.
  • Architect and implement complex multi-agent systems, including planning, decision-making, and execution capabilities.
  • Own, train, build, and deploy cutting-edge deep learning models across all Eightfold products, end to end.
  • Develop and integrate large language models (LLMs) and other state-of-the-art AI techniques to enhance agent autonomy and intelligence.
  • Build robust, scalable, and reliable infrastructure to support the deployment and operation of AI agents at scale.
  • Diagnose and troubleshoot issues in complex distributed environments and optimize system performance.
  • Contribute to the team's technical growth and knowledge sharing.
  • Stay up-to-date with the latest advancements in AI research and agentic AI and apply them to our products.
  • Leverage enterprise data, market data, and user interactions to build intelligent and personalized agent experiences.

Qualifications:
  • Knowledge and passion in machine learning algorithms, Gen AI, LLMs, and natural language processing (NLP).
  • Understanding of agent-based modeling, reinforcement learning, and autonomous systems.
  • Ability to innovate, as proven by a track record of software artifacts or academic publications in applied machine learning.
  • Experience with large language models (LLMs) and their applications in Agentic AI.
  • Proficiency in programming languages such as Python, and experience with machine learning frameworks like TensorFlow or PyTorch.
  • Experience with cloud platforms (AWS) and containerization technologies (Docker, Kubernetes).
  • Understanding of distributed system design patterns and microservices architecture.
  • Excellent problem-solving and data analysis skills.
  • Strong communication and collaboration skills.
  • Master's or Ph.D. in Computer Science, Artificial Intelligence, or a related field, or equivalent years of experience.
  • Min 6-10-+ years of relevant work experience in AI, Machine Learning, and applying data science to real-world use cases.
  • Strong track record of taking systems from prototype to production with a focus on scalability and reliability.
  • Knowledge of fine-tuning strategies (QLORA, DPO) and inference optimization (vLLM, TensorRT-LLM).

Desired Skills & Experience:
  • Research experience in agentic AI or related fields.
  • Experience building and deploying AI agents in real-world applications.


Pay Transparency

Please note this role is categorized as onsite or hybrid in Zone A: Santa Clara, CA The base salary ranges below are provided for pay transparency. Base pay is only one piece of our total compensation package as this role is also eligible for annual bonus and equity awards. Compensation varies depending on a number of factors including qualifications, skills, competencies, experience and zones determined by location.

Zone A: Base annual salary range: $232,000 to $310,000 + annual performance bonus up to 20% + preIPO equity (stock options).

Hybrid Work @ Eightfold: We embrace a hybrid work model that aims to boost collaboration, enhance our culture, and drive innovation through a blend of remote and in-person work. We are committed to creating a dynamic and flexible work environment that nurtures the collaborative spirit of our team. Starting May 1, 2025, employees residing near Santa Clara, CA office location will return to the office three days a week.

Experience our comprehensive benefits with family medical, vision and dental coverage, a competitive base salary, and eligibility for equity awards and discretionary bonuses or commissions.

#LI-Hybrid

About Anywhere Real Estate

Anywhere Real Estate Careers

Joining Anywhere Real Estate offers an unparalleled opportunity to become part of a leading team in the real estate industry, where innovation, leadership, and professional growth are at the forefront of their mission. Anywhere Real Estate is renowned for fostering a culture of diversity and inclusion, making it a prime choice for individuals seeking not only a job but a meaningful career in real estate.

Explore Job Opportunities

Anywhere Real Estate is actively hiring, with numerous job opportunities designed to cater to a variety of skills and professional interests. Whether looking to start a career through an internship or seeking a senior position, Anywhere Real Estate provides a platform where talents are nurtured, and careers are built.

Experience Professional Growth

At Anywhere Real Estate, growth is a fundamental part of the company ethos. Employees are encouraged to expand their horizons through continuous learning and leadership training programs. The company supports career advancement with resources that help individuals gain new skills and take on challenging roles.

Join a Diverse Team

The team at Anyhere Real Estate is composed of dedicated professionals from diverse backgrounds, all working together to innovate and drive success in the real estate market. The company values diversity and offers diversity training to ensure all team members are equipped to contribute to an inclusive environment.

Benefits and Culture

Working at Anywhere Real Estate comes with a comprehensive benefits package that underscores the company's commitment to the well-being and satisfaction of its team members. The culture at Anywhere Real Estate is built on a foundation of respect, integrity, and collaboration, making it an ideal workplace for those who value both personal and professional development.

Networking and Innovation

Employees at Anywhere Real Estate are encouraged to engage in networking opportunities within and beyond the company, enhancing their career prospects and industry knowledge. Innovation is at the core of the company's operations, driving the development of cutting-edge real estate solutions that set industry standards.

How to Apply

To explore available positions at Anywhere Real Estate, prospective candidates are encouraged to visit the Careers section on the company website. Here, they can find information on how to submit a resume, prepare for an interview, and understand what Anywhere Real Estate looks for in potential team members.

Stay Connected

Keep up to date with the latest from Anywhere Real Estate by following their career blog. Gain insights from insider perspectives, and stay informed about new employment opportunities and company news.

Career Development

Anywhere Real Estate is committed to supporting its employees' career paths with unmatched training and certification support. The company's dedication to professional development ensures that every team member has the tools to succeed and make a significant impact in the real estate sector.

Join Anywhere Real Estate

Discover the rewarding career opportunities at Anywhere Real Estate. With a commitment to employee growth, a diverse and inclusive culture, and a drive for innovation, Anywhere Real Estate is the perfect place to advance your career in real estate. Search for open positions that match your skills and interests, and become part of a leading real estate team today.
Learn more about Anywhere Real Estate

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