Senior AI Engineer

Avathon

$130K — $155K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Degree in Computer Science, Statistics, Physics, Mathematics, Engineering, or related field.
  • 2+ years of experience building machine learning models.
  • Strong experience with time series analysis and forecasting techniques (ARIMA, LSTM, etc.).
  • Proficient in Python; experience with R and Matlab is a plus.
  • Familiarity with ML frameworks like TensorFlow and PyTorch.

Responsibilities

  • Build forecasting models for demand planning and optimization.
  • Develop time series models using traditional and modern ML methods.
  • Engage with technical stakeholders to solve AI-related business problems.
  • Design and deploy machine learning models for various applications.
  • Lead all phases of the data science process from exploration to deployment.
  • Create automated anomaly detection systems and track their performance.
  • Communicate complex technical topics effectively to stakeholders.

Benefits

  • Innovative work environment at the forefront of AI technology.
  • Opportunities for professional growth in a fast-scaling startup.
  • Impactful work that drives change across various industries.
Full Job Description
About the Role
As a Senior AI Engineer at Avathon, you will play a key role in designing and delivering advanced AI solutions with a strong emphasis on Generative AI and Large Language Models (LLMs). You will apply scientific rigor to develop scalable, production-ready machine learning systems that drive measurable business impact, working on challenging problems in forecasting, demand planning, renewable energy optimization, anomaly detection, and prescriptive maintenance. With minimum 5 years of industry experience, you are expected to bring strong expertise in statistical modeling, ML engineering, and modern AI architectures, particularly in GenAI and LLM-based applications. This role offers the opportunity to work on high-impact projects that shape next-generation AI capabilities within the organization.
You Will
  • Design, develop, and deploy machine learning and Generative AI solutions to solve complex business problems
  • Build, fine-tune, and optimize Large Language Models (LLMs) and transformer-based architectures for real-world applications
  • Apply rigorous scientific methodologies to experimentation, model evaluation, and performance optimization
  • Develop scalable ML pipelines and production-grade systems in collaboration with Engineering teams
  • Conduct prompt engineering, model alignment, evaluation, and performance benchmarking for GenAI applications
  • Work closely with Product, Engineering, and Business stakeholders to translate ambiguous requirements into data-driven AI solutions
  • Instrument and monitor LLM applications in production using observability tools, tracking cost, latency, quality, and drift
  • Contribute to model governance, responsible AI practices, and performance monitoring in production environments
  • Stay current with advancements in Generative AI, LLM research, and applied machine learning, incorporating relevant innovations into company solutions
You'll Have
  • Master's or PhD in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field
  • Minimum 5 years of hands-on industry experience in AI engineering, machine learning, data science, or applied AI roles
  • Strong experience with Generative AI frameworks and Large Language Models (e.g., transformer architectures, fine-tuning, RAG systems)
  • Proficiency in Python and modern ML/AI libraries such as PyTorch, TensorFlow, Hugging Face, or equivalent ecosystems
  • Solid understanding of statistical modeling, experimentation, and model evaluation methodologies
  • Experience building and deploying ML models into production environments
  • Familiarity with data engineering workflows and cloud-based ML platforms (AWS, GCP, or Azure)
  • Strong problem-solving skills with the ability to work independently on complex and ambiguous problem statements
  • Excellent communication skills with the ability to present technical insights clearly to cross-functional stakeholders
Preferred Qualifications
  • Experience implementing Retrieval-Augmented Generation (RAG), vector databases, and embedding-based search systems
  • Hands-on experience with LLM observability platforms (e.g., Langfuse, LangSmith, Arize Phoenix, Weights & Biases) for tracing, cost tracking, and quality monitoring in production
  • Experience with LLM evaluation frameworks (e.g., RAGAS, DeepEval) and evaluation patterns such as LLM-as-judge and automated regression testing
  • Practical experience deploying LLM applications with guardrails, prompt versioning, hallucination detection, and model drift monitoring
  • Exposure to distributed training, model optimization, and scalable inference architectures
  • Knowledge of MLOps practices, CI/CD for ML (Travis CI, Jenkins), and model lifecycle management
  • Prior experience applying AI solutions in industrial or asset-intensive environments
  • Experience working in fast-paced startup or product-driven environments
  • Industry experience in one or more of the following domains: Mining, Oil & Gas, Aerospace, Supply Chain, Logistics, or Renewable Energy
Benefits & Perks
What are the benefits and perks at Avathon? Below are some highlights we offer to our U.S. full-time employees -- we'd love to connect and share more!
  • Evolving culture with the opportunity to drive new ideas and technology
  • Stock Option Grants
  • Medical Coverage and Parental Leave Plans
  • 401k with Employer Match
  • Monthly Technology Allowance
  • Newly renovated office space located near Pleasanton, CA -- including fully stocked beverage and snack areas

Contract and temporary roles are not eligible for the above benefits.
Compensation
Pay Range: $130k - $155k salary annually. Pay for this position is based on a number of factors including geographic location and may vary depending on job-related knowledge, skills, and experience.

Location: This role is not remote. Candidates must be based in the Bay Area, CA and are expected to report to our Pleasanton office 5 days a week.

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