[Hiring] Senior AI/ML Engineer @Astro Sirens LLC

Role Description

We are currently seeking a Senior AI/ML Engineer with strong experience in modern AI technologies—including Large Language Models (LLMs), Generative AI, and intelligent agent systems—to design and deploy cutting-edge AI solutions.

• Design, develop, and deploy AI/ML solutions leveraging LLMs, NLP, and Generative AI
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and embedding models
• Develop agentic AI systems (multi-step reasoning, tool use, orchestration frameworks)
• Fine-tune, prompt-engineer, and evaluate large language models for production use cases
• Build scalable, end-to-end ML/AI pipelines including data ingestion, preprocessing, model training, and deployment
• Integrate AI solutions into applications via APIs and microservices
• Collaborate with cross-functional teams (data engineers, product managers, and business stakeholders) to define AI-driven solutions
• Implement model monitoring, evaluation frameworks, and guardrails (bias, hallucination mitigation, safety)
• Optimize models and pipelines for performance, scalability, and cost-efficiency in cloud environments
• Translate complex AI outputs into actionable insights for both technical and non-technical audiences
• Contribute to AI best practices, architecture decisions, and internal tooling
• Mentor junior engineers and guide teams on modern AI development patterns

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, Statistics, or a related field
• 5+ years of experience in machine learning, data science, or applied AI roles
• Strong proficiency in Python and ML/AI ecosystems
• Hands-on experience with LLMs and GenAI frameworks (e.g., OpenAI APIs, Hugging Face, LangChain, LlamaIndex, or similar)
• Solid experience with NLP techniques and transformer-based models
• Experience building RAG pipelines and working with vector databases (e.g., Pinecone, Weaviate, FAISS)
• Experience designing or working with agentic workflows (tool calling, multi-agent systems, reasoning chains)
• Strong understanding of ML fundamentals (supervised/unsupervised learning, deep learning, evaluation metrics)
• Experience deploying models into production environments (APIs, batch/real-time systems)
• Familiarity with MLOps/LLMOps practices (model versioning, CI/CD, monitoring, prompt/version management)
• Strong SQL skills and experience with relational databases
• Experience with cloud platforms such as AWS, GCP, or Azure
• Understanding of AI safety, ethics, and data privacy considerations
• Strong communication skills and ability to work with U.S.-based stakeholders

Preferred Qualifications

• Experience with fine-tuning LLMs (LoRA, PEFT, or similar techniques)
• Familiarity with evaluation frameworks for LLMs (e.g., human-in-the-loop, automated evals)
• Experience with Docker, Kubernetes, and scalable AI deployments
• Background in multi-modal AI (text, image, audio models)
• Experience with big data tools like Spark or distributed data processing
• Exposure to cost optimization strategies for LLM-based systems

Benefits

• Paid Time Off (PTO)
• Work From Home
• Professional development opportunities
• Training & Development Programs
• Collaborative and inclusive company culture
• Competitive salary and performance-based bonuses