At UST, we are embarking on an exciting journey to develop cutting-edge artificial intelligence solutions. We are looking for a talented Machine Learning Engineer to join our dynamic team of experts.
The successful candidate will design, train, and deploy machine learning models that power autonomous exception resolution, anomaly detection, and explainable insights. They will work closely with multiple large language model ecosystems, including OpenAI GPT, Anthropic Claude, Google Gemini, and Meta LLaMA.
The key responsibilities of the role include:
* Designing, training, fine-tuning, and deploying machine learning models for production
* Building retrieval-augmented generation pipelines using vector databases and frameworks such as LangChain, LangGraph, and MCP
* Developing prompt engineering, optimization, and safety techniques for agentic large language model interactions
* Collaborating with data engineering teams to maintain data pipelines for machine learning workloads
* Conducting feature engineering and embeddings generation on structured and unstructured data
* Implementing model monitoring, drift detection, and retraining pipelines
* Exploring emerging large language model architectures and multi-agent orchestration patterns
* Cross-functional collaboration with research and development, data science, product, and engineering teams
* Mentoring junior engineers and contributing to best practices in machine learning engineering
The ideal candidate will have a strong background in computer science, data science, or related fields, with 3+ years of experience building and deploying machine learning systems. They should possess advanced English language skills and be proficient in Python, with experience working with PyTorch, TensorFlow, Scikit-Learn, Hugging Face Transformers, and large language models.
A Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or related field is required. The candidate should also have hands-on experience with large language models, including fine-tuning, prompt design, and inference optimization.
* Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or related field
* 3+ years building and deploying machine learning systems
* Advanced English language skills
* Strong Python skills and experience with PyTorch, TensorFlow, Scikit-Learn, Hugging Face Transformers
* Hands-on experience with large language models, including fine-tuning, prompt design, and inference optimization
* Familiarity with at least two of the following: OpenAI GPT, Anthropic Claude, Google Gemini, Meta LLaMA
* Knowledge of vector databases, embeddings, and retrieval-augmented generation pipelines
* Experience working with both structured and unstructured data at scale
* Understanding of SQL and distributed data frameworks like Spark or Ray
* Deep knowledge of the machine learning lifecycle: data preparation, training, evaluation, deployment, and monitoring
* Experience with agentic frameworks (LangChain, LangGraph, MCP, AutoGen)
* Understanding of AI safety, guardrails, and explainability
* Hands-on experience deploying machine learning solutions on AWS, GCP, or Azure
* Familiarity with MLOps practices, including CI/CD, monitoring, and observability
* Background in anomaly detection, fraud/risk modeling, or behavioral analytics
* Contributions to open-source AI/ML projects or research publications
We are excited to welcome talented individuals to our team and look forward to hearing from you!
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