Data Science & Engineering Lead
Particle41
IndiaremotePosted 1 month ago
Skill Required
Data-EngineeringData-ScienceMachine-Learning-EngineeringMLOpsAI-MLData-Engineering-LeadLead-Data-EngineeringLead-Data-EngineerTeam-Lead-(Data-Engineering)Data-and-AI-Technical-LeadData-Engineering-Team-LeadTech-Lead-Data-EngineeringLead-AI-and-Analytics-EngineerSenior-Data-Scientist-LeadSenior-Lead-Data-EngineeringData EngineerEngineeringMachine Learningdata engineeringComputer VisionDeep Learningrelated fieldETLAWSScikit-learnElasticsearchSQL ServerTensorFlowDatabricksPostgreSQLnetworkingautomationLangChainSnowflakeTerraformMLflowDynamoDBbuildingPyTorchAirflowTableauFulltime
Key highlights
- 7+ years of experience required in data science, machine learning, or data engineering.
- Bachelor's degree in a related field required; Master's or PhD preferred.
- AWS or Azure certification strongly preferred.
- Competitive benefits offered.
- Collaborative culture with meaningful work.
- Mentoring responsibilities — guide junior team members in AI/ML best practices.
Role overview
Particle41 is seeking a Data Science & Engineering Lead to drive AI and data innovation within the organization. This hands-on role involves building and deploying high-impact ML models, optimizing data systems, and delivering actionable insights alongside a collaborative team. The ideal candidate brings deep expertise across the full data science and engineering stack, from ML model design and MLOps to cloud infrastructure and lakehouse architectures.
Responsibilities
- 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, Databricks, and Azure ML Studio.
- Develop and optimize business intelligence dashboards with tools like Tableau, QuickSight, and PowerBI for actionable insights.
- Implement GPU acceleration and CUDA for model training and optimization.
- Mentor junior team members in cutting-edge AI/ML techniques and best practices.
Requirements
- Proven expertise in both supervised and unsupervised ML, advanced deep learning, including TensorFlow, PyTorch, and neural network architectures (e.g., CNN, GAN, Transformers).
- Hands-on experience with machine learning libraries and tools such as Scikit-learn, Pandas, and Numpy.
- Proficiency in AI model development using LLM libraries (e.g., Langchain, Huggingface, OpenAI).
- Strong MLOps skills, with experience deploying scalable pipelines in production using tools like Sagemaker, Databricks, and Azure ML Studio.
- Advanced skills in big data frameworks like Apache Spark, Glue, and EMR for distributed model training.
- Expertise in ETL processes and data pipeline development with tools like Airflow, DBT, and Airbyte.
- Strong knowledge in lakehouse architectures (Delta/Iceberg) and experience with data quality frameworks like Great Expectations.
- Proficiency in cloud platforms (AWS preferred or Azure), with a deep understanding of services like IAM, VPC networking, Lambda, API Gateway, Batch, Kinesis, and Kafka.
- Proficiency with Infrastructure as Code (IaC) tools such as Terraform or CloudFormation for automation.
- Advanced skills in GPU acceleration, CUDA, and distributed model training.
- Demonstrated ability to architect and deploy scalable machine learning and data-intensive systems.
- Proficiency in database modeling for OLTP/OLAP systems and expertise with relational and NoSQL databases.
- Strong mentoring skills, with a proven track record of guiding junior team members in AI/ML best practices.
- Bachelor's degree in a related field (required).
- 7+ years of experience in data science, machine learning, or data engineering.
- Strong communication and leadership skills with experience working cross-functionally to deliver high-impact data solutions.
Nice to have
- Master's or PhD in Data Science or a related field.
- AWS or Azure certification.
Additional details
- Originally posted on Himalayas.
- Our core values of Empowering, Leadership, Innovation, Teamwork, and Excellence drive everything we do to achieve the ultimate outcomes for our clients. Empowering Leadership for Innovation in Teamwork with Excellence (ELITE): E - Empowering: Enabling individuals to reach their full potential; L - Leadership: Taking initiative and guiding each other toward success; I - Innovation: Embracing creativity and new ideas to stay ahead; T - Teamwork: Collaborating with empathy to achieve common goals; E - Excellence: Striving for the highest quality in everything we do.
- We seek team members who embody these values and are committed to contributing to our mission. Particle41 welcomes individuals from all backgrounds who are committed to our mission and values.
- We provide equal employment opportunities to all employees and applicants, ensuring that hiring and employment decisions are based on merit and qualifications without discrimination based on race, color, religion, caste, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, local, or international laws. This policy applies to all aspects of employment and hiring.
- We appreciate your interest and encourage applicants from these regions to apply. If you need any assistance during the application or interview process, please feel free to reach out to us.