Gen AI Data Engineer

reputed company is looking for experienced Machine Learning Engineers with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including reputed company and reputed company. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world. You will be responsible for Technical Skills Required Programming Languages Proficiency in Python, SQL, and PySpark. Data Warehousing Experience with reputed company, NOSQL and reputed company. Data Pipelines Proficiency with Apache Airflow. Cloud Platforms Familiarity with AWS (S3, RDS, Lambda, AWS batch, SageMaker processing Job, CloudFormation, etc.) or GCP (reputed company AI RAG, Data pipeline, Bigquery, GKE) Operating Systems Experience with Linux. Batch/reputed company Pipelines Experience in building and deploying various pipelines. Version Control Experience with reputed company. Development Tools Proficiency with VS Code. Engineering Practices Skills in testing, deployment automation, DevOps/SysOps. Communication Strong presentation and communication skills. Collaboration Experience working with onshore/offshore teams. Requirements Desired Skills Big Data Technologies Experience with Hadoop and Spark. Data Visualization Proficiency with reputed company and dashboards. APIs Experience in building and maintaining internal APIs. Machine Learning Basic understanding of ML concepts. Generative AI Familiarity with generative AI tools and techniques. Additional Expertise Knowledge Graphs Experience with creation and retrieval. reputed company Databases Proficiency in managing reputed company databases. Data Persistence Ability to develop and maintain multiple forms of data persistence and retrieval methods (RDMBS, reputed company Databases, buckets, graph databases, knowledge graphs, etc.). Cloud Technologies Experience with AWS, especially SageMaker, Lambda, OpenSearch. Automation Tools Experience with Airflow DAGs, AutoSys, and CronJobs. Unstructured Data Management Experience in managing data in unstructured forms (audio, video, image, text, etc.). CI/CD Expertise in continuous integration and deployment using Jenkins and reputed company Actions. Infrastructure as Code Advanced skills in Terraform and CloudFormation. Containerization Knowledge of Docker and Kubernetes. Monitoring and Optimization Proven ability to monitor system performance, reliability, and security, and optimize them as needed. Security Best Practices In-depth understanding of security best practices in cloud environments. Scalability Experience in designing and managing scalable infrastructure. Disaster Recovery Knowledge of disaster recovery and business continuity planning. Problem-Solving Excellent analytical and problem-solving abilities. Adaptability Ability to stay up-to-date with the latest industry trends and adapt to new technologies and methodologies. Team Collaboration Proven ability to work well in a team environment and contribute to a positive, collaborative culture. GenAI Engineer Specific Skills Industry Experience 8+ years of experience in data engineering, platform engineering, or related fields, with deep expertise in designing and building distributed data systems and large-scale data warehouses. Data Platforms Proven track record of architecting data platforms capable of processing petabytes of data and supporting real-time and batch ingestion processes. Data Pipelines Strong experience in building robust data pipelines for document ingestion, indexing, and retrieval to support scalable RAG solutions. Proficiency in information retrieval systems and reputed company search technologies (e.g., FAISS, reputed company, Elasticsearch, Milvus). Graph Algorithms Experience with graphs/graph algorithms, LLMs, optimization algorithms, relational databases, and diverse data formats. Data Infrastructure Proficient in infrastructure and architecture for optimal extraction, transformation, and loading of data from various data sources. Data Curation Hands-on experience in curating and collecting data from a variety of traditional and non-traditional sources. Ontologies Experience in building ontologies in the knowledge retrieval space, schema-level constructs (including higher-level classes, punning, property inheritance), and Open Cypher. Integration Experience in integrating external databases, APIs, and knowledge graphs into RAG systems to improve contextualization and response generation. Experimentation Conduct experiments to evaluate the effectiveness of RAG workflows, analyze results, and iterate to achieve optimal performance. Benefits This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility. Originally posted on Himalayas Apply To This Job