Engineering, or a related field 3+ years of experience in machine learning operations, data engineering, or related roles AWS Proficiency: Strong understanding of AWS services (e.g., EC2, S3, Lambda, SageMaker, ECS) and cloud infrastructure management Programming and ML Frameworks: Proficiency in Python and experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch CI/CD Experience: Experience More ❯
Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker/Bedrock) Deep understanding of distributed systems and microservices architecture Expert in data pipeline platforms (Apache Kafka, Airflow, Spark) Proficient in both SQL (PostgreSQL, MySQL) and NoSQL (Elasticsearch, MongoDB More ❯
Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker/Bedrock) Deep understanding of distributed systems and microservices architecture Expert in data pipeline platforms (Apache Kafka, Airflow, Spark) Proficient in both SQL (PostgreSQL, MySQL) and NoSQL (Elasticsearch, MongoDB More ❯
image processing workflows, deep learning pipelines, and model evaluation. Familiarity with MLflow for tracking experiments, managing model lifecycle, or deploying models. Experience with AWS services such as S3, EC2, SageMaker, Lambda, or similar tools for model deployment and data pipelines. What you'll be doing: Research and develop solutions to complex business problems, working with large, unstructured datasets. Apply More ❯
data pipelines and ETL processes for data extraction and transformation. Apply statistical and machine learning techniques for predictive and segmentation analyses. Develop KPIs and dashboards for decision-making using Amazon QuickSight. Perform exploratory data analysis to identify trends and insights. Collaborate with data engineers to optimize data architecture and governance. Requirements: Bachelor's or master's in Computer Science … analytical and problem-solving skills. Experience with social media analytics and user behavior. Familiarity with big data tools like Hadoop, Spark, Kafka. Knowledge of AWS ML services such as SageMaker and Comprehend. Understanding of data governance and security in AWS. Excellent communication and teamwork skills. Attention to detail and ability to meet deadlines. Compensation: This is an equity-only More ❯
collaborate across disciplines. Experience and skills we'd love: Familiarity with MLflow for tracking experiments, managing model lifecycle, or deploying models. Experience with AWS services such as S3, EC2, SageMaker, Lambda, or similar tools for model deployment and data pipelines. Computer Vision Expertise: Practical experience or exposure to modern computer vision models and techniques such as ResNet, YOLO, Vision More ❯
