About the Role
We are seeking a highly skilled AI/ML Engineer with strong hands-on experience in building machine learning models Large Language Models (LLMs) and agentic AI solutions. The ideal candidate should have deep expertise in Python solid understanding of Java and proven experience working on GCP (BigQuery). The role focuses on end-to-end model development including designing training optimizing and deploying ML/LLM-based systems into production.
Key Responsibilities
1. Model Development & Deployment
- Design develop train and test machine learning models LLMs and advanced AI solutions.
- Work on Retrieval-Augmented Generation (RAG) pipelines to enhance model accuracy and contextual performance.
- Convert models into APIs or microservices for scalable production deployment.
- Optimize models for performance latency and cost-efficiency in production environments.
2. Technical Development
- Build and maintain reusable ML code pipelines and components using Python.
- Work with structured and unstructured data implementing feature engineering and data preprocessing.
- Collaborate with cross-functional teams (Data Engineering Cloud Product) to integrate AI models into enterprise systems.
3. Tools Platforms & MLOps
- Use Google Cloud Platform (GCP) services specifically BigQuery for data processing and model integration.
- Apply version control using Git and follow CI/CD best practices for ML workflows.
- Work with MLOps tools such as MLFlow for experiment tracking reproducibility and model lifecycle management.
Required Skills & Experience
Core Technical Skills
- Python Expert level (mandatory)
- Java Working proficiency
- Strong knowledge of SQL and hands-on experience with NoSQL databases.
- Experience with deep learning and ML frameworks such as:
AI/ML Expertise
- 3 years of Experience building and tuning LLMs including prompt engineering fine-tuning and embedding models.
- Hands-on exposure to RAG architectures.
- Understanding of agentic AI workflows and autonomous agents.
Cloud & Tools
- Experience working on GCP especially with BigQuery.
- Knowledge of Git and standard DevOps practices.
- Familiarity with MLOps tooling (MLFlow model registries experiment tracking).
Good to Have
- Exposure to vector databases (FAISS Pinecone Chroma).
- Experience with Docker/Kubernetes for model deployment.
- Understanding of microservices architecture.
- Knowledge of API development frameworks (FastAPI Flask Spring Boot).
SYNECHRONS DIVERSITY & INCLUSION STATEMENT
Diversity & Inclusion are fundamental to our culture and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity Equity and Inclusion (DEI) initiative Same Difference is committed to fostering an inclusive culture promoting equality diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger successful businesses as a global company. We encourage applicants from across diverse backgrounds race ethnicities religion age marital status gender sexual orientations or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements mentoring internal mobility learning and development programs and more.
All employment decisions at Synechron are based on business needs job requirements and individual qualifications without regard to the applicants gender gender identity sexual orientation race ethnicity disabled or veteran status or any other characteristic protected by law.
Candidate Application Notice
Required Experience:
Senior IC
About the RoleWe are seeking a highly skilled AI/ML Engineer with strong hands-on experience in building machine learning models Large Language Models (LLMs) and agentic AI solutions. The ideal candidate should have deep expertise in Python solid understanding of Java and proven experience working o...
About the Role
We are seeking a highly skilled AI/ML Engineer with strong hands-on experience in building machine learning models Large Language Models (LLMs) and agentic AI solutions. The ideal candidate should have deep expertise in Python solid understanding of Java and proven experience working on GCP (BigQuery). The role focuses on end-to-end model development including designing training optimizing and deploying ML/LLM-based systems into production.
Key Responsibilities
1. Model Development & Deployment
- Design develop train and test machine learning models LLMs and advanced AI solutions.
- Work on Retrieval-Augmented Generation (RAG) pipelines to enhance model accuracy and contextual performance.
- Convert models into APIs or microservices for scalable production deployment.
- Optimize models for performance latency and cost-efficiency in production environments.
2. Technical Development
- Build and maintain reusable ML code pipelines and components using Python.
- Work with structured and unstructured data implementing feature engineering and data preprocessing.
- Collaborate with cross-functional teams (Data Engineering Cloud Product) to integrate AI models into enterprise systems.
3. Tools Platforms & MLOps
- Use Google Cloud Platform (GCP) services specifically BigQuery for data processing and model integration.
- Apply version control using Git and follow CI/CD best practices for ML workflows.
- Work with MLOps tools such as MLFlow for experiment tracking reproducibility and model lifecycle management.
Required Skills & Experience
Core Technical Skills
- Python Expert level (mandatory)
- Java Working proficiency
- Strong knowledge of SQL and hands-on experience with NoSQL databases.
- Experience with deep learning and ML frameworks such as:
AI/ML Expertise
- 3 years of Experience building and tuning LLMs including prompt engineering fine-tuning and embedding models.
- Hands-on exposure to RAG architectures.
- Understanding of agentic AI workflows and autonomous agents.
Cloud & Tools
- Experience working on GCP especially with BigQuery.
- Knowledge of Git and standard DevOps practices.
- Familiarity with MLOps tooling (MLFlow model registries experiment tracking).
Good to Have
- Exposure to vector databases (FAISS Pinecone Chroma).
- Experience with Docker/Kubernetes for model deployment.
- Understanding of microservices architecture.
- Knowledge of API development frameworks (FastAPI Flask Spring Boot).
SYNECHRONS DIVERSITY & INCLUSION STATEMENT
Diversity & Inclusion are fundamental to our culture and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity Equity and Inclusion (DEI) initiative Same Difference is committed to fostering an inclusive culture promoting equality diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger successful businesses as a global company. We encourage applicants from across diverse backgrounds race ethnicities religion age marital status gender sexual orientations or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements mentoring internal mobility learning and development programs and more.
All employment decisions at Synechron are based on business needs job requirements and individual qualifications without regard to the applicants gender gender identity sexual orientation race ethnicity disabled or veteran status or any other characteristic protected by law.
Candidate Application Notice
Required Experience:
Senior IC
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