数据科学与工程负责人
Data Science & Engineering Lead
Data Science & Engineering Lead
作为我们的Data Science & Engineering Lead，引领AI和数据创新。你将与我们才华横溢的团队紧密合作，构建和部署高影响力的ML模型，优化数据系统，并推动可操作的洞察。如果你精通Databricks、Spark和Azure等高级AI工具，并对机器学习和工程领域充满热情，我们希望你加入我们的团队。加入我们，从事有意义的工作，融入协作的文化，并享受具有竞争力的福利。
在这一职位中，你将：
- 设计并实现监督和非监督ML模型（例如OLS、逻辑回归、集成方法），解决实际业务问题。
- 领导神经网络先进架构的模型开发，如ANN、CNN、RNN、GAN、Transformer和RESNet。
- 使用NLTK和基于神经网络的语言模型推动自然语言处理（NLP）的发展。
- 监督计算机视觉模型的开发，利用OpenCV进行实际应用。
- 领导时间序列建模项目，用于预测和异常检测。
- 使用检索增强生成（RAG）、思维链（CoT）和对齐模型（MOA）等AI技术提升模型性能。
- 构建和维护适用于流式和批处理的可扩展数据管道。
- 使用Delta/Iceberg和青铜-银-金架构设计和优化湖仓解决方案。
- 使用Airflow、DBT和Airbyte等工具领导ETL流程的开发，以支持数据流动和转换。
- 使用Snowflake、SQL Server、PostgreSQL和MySQL设计和优化OLTP和OLAP系统的数据库模型。
- 开发NoSQL解决方案，利用MongoDB、DynamoDB和ElasticSearch处理非结构化数据。
- 领导云基础设施的建设，特别是在AWS（优先）或Azure上，使用Lambda、API Gateway、批处理、Kinesis和Kafka等服务。
- 使用Sagemaker、Databricks和Azure ML Studio等平台监督MLOps管道，实现ML模型的稳健生产部署。
- 使用Tableau、QuickSight和PowerBI等工具开发和优化商业智能仪表板，提供可操作的洞察。
- 实现GPU加速和CUDA用于模型训练和优化。
- 指导初级团队成员掌握前沿的AI/ML技术和最佳实践。
我们看重的技能和经验：
- 在监督和非监督机器学习、高级深度学习方面有显著经验，包括TensorFlow、PyTorch等。
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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, 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.
Skills and Experience We Value:
- 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), with a Master’s or PhD in Data Science or a related field (preferred).
- 7+ years of experience in data science, machine learning, or data engineering.
- AWS or Azure certification (strongly preferred).
- Strong communication and leadership skills with experience working cross-functionally to deliver high-impact data solutions.
About Particle41Our 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 at .
Originally posted on Himalayas