Responsibilities
- Design, train, fine-tune, deploy, and optimize large language models and multimodal agents for enterprise automation.
- Build scalable cloud pipelines for training, inference, retraining, model monitoring, versioning, and continuous deployment.
- Develop RAG, multimodal, and knowledge-based AI systems supporting operational workflows and decision support.
- Conduct model evaluation, bias and fairness assessment, interpretability checks, security assessments, and performance tuning.
- Collaborate with data scientists, platform engineers, business stakeholders, and business units to translate use cases into operational AI systems.
- Troubleshoot inference latency, retraining workflows, and deployment environments at enterprise scale.
- Document model architecture, training, deployment, operational metrics, and procedures for audit, compliance, and governance.
- Mentor junior AI engineers and promote responsible AI deployment practices.
Requirements
- Bachelor's or master's degree in Data Science, Computer Science, AI, or a related technical field.
- At least 4 years of experience supporting enterprise AI/ML solutions involving large language models, RAG, and multimodal agents.
- Extensive hands-on Python experience supporting the training, fine-tuning, and inference of large AI models.
- Expertise with PyTorch and TensorFlow for training, deploying, and optimizing deep learning models.
- Experience with LLMs such as GPT, Claude, Llama, or Gemini, including prompt engineering, fine-tuning, and deployment.
- Experience deploying scalable AI models on AWS, Azure, or GCP and managing model lifecycles and inference environments.
- Experience with model evaluation, responsible AI, fairness, security, compliance, data privacy, and operational monitoring.
- Experience with MLflow, Kubeflow, MLOps pipelines, data preparation, feature engineering, and scalable inference.
- Preferred experience with Hugging Face Transformers, LangChain, Docker, Kubernetes, TFX, multimodal processing, and cloud or responsible AI certifications.
- Strong analytical, troubleshooting, stakeholder communication, documentation, organizational, and mentoring skills.
Benefits
- Hybrid work arrangement requiring three days per week at the client office.
- Flexible workplace arrangements, mentoring, internal mobility, and learning and development programs.
- Equal opportunity workplace with a stated commitment to diversity, equity, and inclusion.
Tech Stack
Categories
About Synechron
At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron’s progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. Through research and development initiatives in our Synechron Labs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile-first applications and more. Over the last 20+ years, our company has been honored with multiple employer awards, recognizing our commitment to our talented teams. With top clients to boast about, Synechron has a global workforce of 14,000+, and has 55 offices in 20 countries within key global markets. For more information on the company, please visit our website:www.synechron.com.