Submitting more applications increases your chances of landing a job.

Here’s how busy the average job seeker was last month:

Opportunities viewed

Applications submitted

Keep exploring and applying to maximize your chances!

Looking for employers with a proven track record of hiring women?

Click here to explore opportunities now!
We Value Your Feedback

You are invited to participate in a survey designed to help researchers understand how best to match workers to the types of jobs they are searching for

Would You Be Likely to Participate?

If selected, we will contact you via email with further instructions and details about your participation.

You will receive a $7 payout for answering the survey.


User unblocked successfully
https://bayt.page.link/LJeRoNZ16GYihhUXA
Back to the job results

Senior AI/ML Engineer (LLM, GenAI, and Agentic Systems)

4 days ago 2026/09/03
Remote
Other Business Support Services
Create a job alert for similar positions
Job alert turned off. You won’t receive updates for this search anymore.

Job description

Astro Sirens is an IT staffing agency based in Austin, Texas.
We connect talented professionals from around the world with U.
S. companies, offering exciting opportunities to work on innovative, high-impact projects.
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.
Responsibilities 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 Paid Time Off (PTO) Work From Home Professional development opportunities Training & Development Programs Collaborative and inclusive company culture Competitive salary and performance-based bonuses 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
This job post has been translated by AI and may contain minor differences or errors.

You’ve reached the maximum limit of 15 job alerts. To create a new alert, please delete an existing one first.
Job alert created for this search. You’ll receive updates when new jobs match.
Are you sure you want to unapply?

You'll no longer be considered for this role and your application will be removed from the employer's inbox.