About Aizen
At Aizen, we’re on a mission to make AI less complicated and more powerful. Our end-to-end platform streamlines the entire AI pipeline—from data ingestion and orchestration to model training, deployment, and monitoring—so businesses can focus on what really matters: building and scaling awesome AI solutions without the headache.
We started Aizen because we were tired of clunky AI workflows and patchwork solutions that hinder AI adoption. Today, companies of all sizes—from emerging startups to Fortune 500 enterprises—trust us to power their AI pipelines and scale effortlessly. By redefining how AI is built, deployed, and managed, we’re making AI more accessible and impactful than ever. If you love building cool tech, solving real-world problems, and working with a world-class engineering team, we’d love to meet you.
About the Team
Aizen was founded by a team of serial entrepreneurs with deep expertise in data storage, distributed systems, and real-time AI architecture. With experience building and scaling tech companies—some leading to successful $1B+ exits—our team understands what it takes to create a best-in-class product and company. We’ve designed Aizen from the ground up to simplify the AI pipeline, optimize performance, and make AI truly accessible to enterprises of all sizes.
About the Role
As a Machine Learning Engineer at Aizen, you’ll be instrumental in building and optimizing the AI pipelines that power our end-to-end AI platform. You’ll work across the stack, from data ingestion and model training to real-time inference and monitoring, ensuring seamless AI deployment at scale. Whether you’re an entry-level engineer eager to grow or a senior engineer ready to lead high-impact projects, this role offers the opportunity to tackle complex ML challenges, enhance automation, and help shape the future of AI infrastructure.
Core Responsibilities
AI Pipeline Development – Design, build, and optimize end-to-end AI pipelines for data ingestion, training, deployment, and real-time inference, ensuring seamless integration with MLOps and infrastructure systems.
Model Training & Deployment – Implement training and fine-tuning workflows for ML models, optimizing for efficiency, scalability, and reproducibility across cloud, on-prem, and edge environments.
Backend & API Development – Develop and integrate scalable backend services and APIs for model inference, batch processing, and real-time AI applications, collaborating with data and product teams.
Observability & Model Monitoring – Build monitoring and logging tools to track model performance, drift, and latency, developing automated alerts and continuous retraining workflows to maintain AI accuracy.
LLM Development & Optimization – Build and deploy LLM-based applications, integrating APIs from providers like OpenAI, Anthropic, and Cohere, and optimizing for fine-tuning, inference, and cost efficiency.
Advanced AI & ML Development – Research and implement cutting-edge ML techniques, experimenting with LLM fine-tuning, embeddings, and model architectures to enhance AI performance and efficiency.
Preferred Qualifications (Applicable to All Levels)
Proficiency in Python and ML frameworks – Strong coding skills in Python, with experience using frameworks such as PyTorch, TensorFlow, or JAX for ML and DL applications.
Cloud & MLOps Experience – Familiarity with cloud platforms like AWS, GCP, or Azure and experience deploying and managing ML models in production environments.
Strong Problem-Solving & Collaboration Skills – Ability to tackle complex ML challenges, iterate quickly, and work closely with cross-functional teams including engineering, product, and data science.
Understanding of MLOps & Model Deployment – Experience with CI/CD for ML, model serving, and monitoring, using tools like MLflow, Kubernetes, or Ray.
Experience with LLMs & NLP (Nice to Have) – Knowledge of transformer-based models, fine-tuning techniques, and APIs from OpenAI, Anthropic, or Cohere is a plus.
Entry-Level Qualifications
1+ Year(s) of Experience in AI/ML Development – Experience with training and deploying ML models, either in a professional setting, academic setting, research projects, or internships.
Experimental Mindset & Eagerness to Learn – Comfortable iterating on models, testing different approaches, and staying up-to-date with state-of-the-art AI advancements.
Senior-Level Qualifications
4+ Years of Experience in AI/ML Engineering – Proven ability to ship ML/AI capabilities to production, optimizing for scalability, latency, and reliability.
Experience Building AI/ML Infra at Scale – Background in distributed systems, real-time inference, and MLOps automation for enterprise-level AI applications.
Technical Leadership & Mentorship – Ability to drive architectural decisions, mentor junior engineers, and lead cross-functional initiatives to enhance AI capabilities at scale.
Benefits
At Aizen, we believe great work starts with taking care of our team. We offer competitive compensation, flexible work options, and comprehensive benefits to support you both personally and professionally.
Competitive Compensation – We offer a competitive salary along with meaningful equity, so you can directly share in Aizen’s success.
Remote-Friendly Culture – Work from wherever you’re most productive, with the option to collaborate in person at our office hubs.
Flexible PTO – Take the time you need with our generous paid time off policy—because work-life balance matters.
Comprehensive Health Plans – We provide medical, dental, and vision coverage for you and your family.
Paid Parental Leave – Enjoy fully paid parental leave to spend time with your growing family.
401(k) Plan (U.S. Specific) – We help you plan for the future with a company-supported 401(k).
Equal Opportunity
Aizen is an equal opportunity employer committed to fostering a diverse and inclusive workplace. We welcome applicants of all backgrounds and do not discriminate based on race, gender, age, disability, or any other protected status.