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Particle41

Provides expert application, DevOps, ML teams

Data Science & Engineering Lead

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeRemote in IndiaNo salary listedRemote

About the Job

Requirements

  • Proven expertise in supervised and unsupervised machine learning, advanced deep learning, TensorFlow, PyTorch, and neural network architectures such as CNNs, GANs, and Transformers.
  • Hands-on experience with machine learning libraries and tools including Scikit-learn, Pandas, and NumPy.
  • Proficiency in AI model development using large language model libraries such as LangChain, Hugging Face, and OpenAI.
  • Strong MLOps skills and experience deploying scalable production pipelines using SageMaker, Databricks, and Azure ML Studio.
  • Advanced skills in big data frameworks such as Apache Spark, Glue, and EMR for distributed model training.
  • Expertise in ETL processes and data pipeline development using Airflow, dbt, and Airbyte.
  • Knowledge of lakehouse architectures such as Delta and Iceberg, and experience with data quality frameworks such as Great Expectations.
  • Proficiency in AWS or Azure cloud platforms, including IAM, VPC networking, Lambda, API Gateway, Batch, Kinesis, and Kafka.
  • Proficiency with Infrastructure as Code tools such as Terraform or CloudFormation.
  • Advanced skills in GPU acceleration, CUDA, and distributed model training.
  • Ability to architect and deploy scalable machine learning and data-intensive systems.
  • Proficiency in database modeling for OLTP and OLAP systems and expertise with relational and NoSQL databases.
  • Strong mentoring skills and a proven track record of guiding junior team members in AI/ML best practices.
  • A bachelor's degree in a related field is required.
  • At least 7 years of experience in data science, machine learning, or data engineering.
  • Strong communication and leadership skills and experience working cross-functionally to deliver data solutions.

Responsibilities

  • Design and implement supervised and unsupervised machine learning models, including OLS, logistic regression, and ensemble methods, to solve business problems.
  • Lead model development for neural network architectures including ANN, CNN, RNN, GAN, Transformers, and ResNet.
  • Drive natural language processing advancements using NLTK and neural-based language models.
  • Oversee development of computer vision models using OpenCV.
  • Lead time-series modeling projects for forecasting and anomaly detection.
  • Use retrieval-augmented generation, chain of thought, and model of alignment techniques to enhance model performance.
  • Build and maintain scalable data pipelines for streaming and batch processing.
  • Architect and optimize lakehouse solutions using Delta or Iceberg and bronze-silver-gold architectures.
  • Lead development of ETL processes using Airflow, dbt, and Airbyte for data flow and transformation.
  • Design and optimize database models for OLTP and OLAP systems using Snowflake, SQL Server, PostgreSQL, and MySQL.
  • Develop NoSQL solutions using MongoDB, DynamoDB, and Elasticsearch.
  • Lead cloud infrastructure development, particularly in AWS or Azure, using services such as Lambda, API Gateway, Batch, Kinesis, and Kafka.
  • Oversee MLOps pipelines for production deployment of machine learning models using SageMaker, Databricks, and Azure ML Studio.
  • Develop and optimize business intelligence dashboards using Tableau, QuickSight, and Power BI.
  • Implement GPU acceleration and CUDA for model training and optimization.
  • Mentor junior team members in AI/ML techniques and best practices.

Desired Qualifications

  • A master's or PhD in Data Science or a related field is preferred.
  • AWS or Azure certification is strongly preferred.

About the Company

Particle41

Provides expert application, DevOps, ML teams

Particle41 builds expert teams across software development, DevOps, and machine learning to strengthen a client’s capabilities. It assembles cross-functional teams that integrate into client projects, guiding work with clear communication and predictable timelines to drive fast progress. The service emphasizes specialized, high-caliber teams that augment the client’s own capabilities with speed, transparency, and forward planning. Its goal is to amplify a client’s business by delivering dependable teams that advance critical development, operations, and ML initiatives.

Company size
51-200
Company stage
Not listed
Total funding
Not listed
Headquarters
Frisco, TX
Founded
2015

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