Software Engineer, AI ML

As a crucial member of our team, you’ll play a pivotal role across the entire machine learning lifecycle, contributing to our conversational AI bots, RAG system and traditional ML problem solving for our observability platform. Your tasks will encompass both operational and engineering aspects, including building production-ready inference pipelines, deploying and versioning models, and implementing continuous validation processes. On the LLM side you’ll fine-tune generative AI models, design agentic language chains, and prototype recommender system experiments.

What you’ll do:

• Fine-tuning generative AI models to enhance performance.
• Designing AI Agents for conversational AI applications.
• Experimenting with new techniques to develop models for observability use cases
• Building and maintaining inference pipelines for efficient model deployment.
• Managing deployment and model versioning pipelines for seamless updates.
• Developing tooling to continuously validate models in production environments.

This role requires:

• 2+ Years Demonstrated proficiency in software engineering design practices.
• Bachelor’s or advanced degree in Computer Science, Engineering, Mathematics, or a related field. Advanced degree (Master’s or Ph.D.) preferred.
• Experience working with transformer models and text embeddings.
• Proven track record of deploying and managing ML models in production environments.
• Familiarity with common ML/NLP libraries such as PyTorch, Tensorflow, HuggingFace Transformers, and SpaCy.
• preferred experience developing production-grade applications in Python.
• Proficiency in Kubernetes and containers.
• Familiarity with concepts/libraries such as sklearn, kubeflow, argo, and seldon.
• Expertise in Python, C++, Kotlin, or similar programming languages.
• Experience designing, developing, and testing scalable distributed systems.
• Familiarity with message broker systems (e.g., Kafka, RabbitMQ).
• Knowledge of application instrumentation and monitoring practices.
• Experience with ML workflow management, like AirFlow, Sagemaker, etc.
• Bonus: Familiarity with the AWS ecosystem.
• Bonus: Past projects involving the construction of agentic language chains.

Bonus points if you have:

• Experience in LangChain

Fostering a diverse, welcoming and inclusive environment is important to us. We work hard to make everyone feel comfortable bringing their best, most authentic selves to work every day. We celebrate our talented Relics’ different backgrounds and abilities, and recognize the different paths they took to reach us – including nontraditional ones. Their experiences and perspectives inspire us to make our products and company the best they can be. We’re looking for people who feel connected to our mission and values, not just candidates who check off all the boxes.