Responsibilities
- Lead the design, training, fine-tuning, and deployment of LLMs and multimodal agents for enterprise automation and insights.
- Build scalable cloud-based AI pipelines for training, real-time inference, retraining, model monitoring, versioning, and deployment.
- Collaborate with data scientists, platform engineers, business stakeholders, and business units to translate use cases into operational AI systems.
- Conduct prompt engineering, model evaluation, bias and fairness assessments, interpretability checks, security reviews, and performance tuning.
- Automate MLOps workflows and support responsible AI, compliance, governance, and audit-readiness standards.
- Develop and support data pipelines for multimodal, retrieval-augmented, and knowledge-based AI systems.
- Troubleshoot inference latency, retraining workflows, and deployment environments at enterprise scale.
- Document model architecture, training, tuning, deployment procedures, and operational metrics.
- Guide and mentor junior AI engineers and promote responsible AI engineering 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, retrieval-augmented systems, and multimodal agents.
- Extensive hands-on experience with Python, including large-model training, fine-tuning, and inference.
- Proven 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 AI models in AWS, Azure, or GCP cloud environments and managing scalable inference.
- Experience with model lifecycle, orchestration, versioning, monitoring, MLOps, responsible AI, fairness, security, and compliant enterprise systems.
- Experience with data preparation, feature engineering, model validation, and multimodal or RAG architectures.
- Preferred experience with MLflow, Kubeflow, TFX, AI evaluation and bias-mitigation tools, and cloud or responsible AI certifications.
- Strong analytical, troubleshooting, stakeholder communication, documentation, organizational, leadership, and strategic-thinking skills.
Benefits
- Hybrid work arrangement requiring three days per week at a client office.
- Flexible workplace arrangements, mentoring, internal mobility, and learning and development programs.
- Inclusive and 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.