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Data Science & Engineering Lead

Particle41India🌍 Remote
Full-time3-7
👁️ 0 views📝 0 applicationsPosted 9/1/2026Expires 10/1/2026
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Job Description

Data Science & Engineering Lead Lead the charge in AI and data innovation as our Data Science & Engineering Lead . Here, you’ll work hands-on with our talented team to build and deploy high-impact ML models, optimize our data systems, and drive actionable insights.

If you’re skilled in advanced AI tools like Databricks, Spark, and Azure, and excited to push boundaries in machine learning and engineering, we want you on our team. Join us for meaningful work, a collaborative culture, and competitive benefits.

In This Role, You Will: Design and implement supervised and unsupervised ML models (e. g. , OLS, Logistic Regression, Ensemble Methods) to solve real-world business problems. Lead model development for advanced architectures in neural networks, such as ANN, CNN, RNN, GAN, Transformers, and RESNet.

Drive NLP advancements with tools like NLTK and neural-based language models. Oversee the development of computer vision models, utilizing OpenCV for real-world applications. Lead time-series modeling projects for forecasting and anomaly detection.

Utilize AI techniques like Retrieval-Augmented Generation (RAG), Chain of Thought (CoT), and Model of Alignment (MOA) to enhance model performance. Build and maintain scalable data pipelines for both streaming and batch processing.

Architect and optimize lakehouse solutions using Delta/Iceberg and bronze-silver-gold architectures. Lead the development of ETL processes with tools like Airflow, DBT, and Airbyte to support data flow and transformation.

Design and optimize database models for OLTP and OLAP systems using Snowflake, SQL Server, PostgreSQL, and MySQL. Develop NoSQL solutions, leveraging MongoDB, DynamoDB, and ElasticSearch for unstructured data.

Lead efforts in building cloud infrastructure, particularly in AWS (preferred) or Azure, using services such as Lambda, API Gateway, Batch processing, Kinesis, and Kafka. Oversee MLOps pipelines for robust deployment of ML models in production with platforms like Sagemaker, Da

Required Skills

Machine LearningData SciencePythonSupervised LearningUnsupervised LearningNeural NetworksNLPComputer VisionTime-Series AnalysisETLData PipelinesDatabricksSparkAzureDelta LakeIcebergAirflowDBTSnowflakeSQLNLTKOpenCVRetrieval-Augmented GenerationChain of ThoughtModel of AlignmentAirbyteKafkaPostgreSQLMySQLMongoDBDynamoDBElasticSearchLambdaAPI GatewayBatch Processing

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