We are Data Nerds. Astronomer & Amazon Consulting Partners.
machine learning • data science • deep learning • artificial intelligence • consulting
51 - 200
November 16, 2023
Airflow
Apache
AWS
Big Data
CI/CD
Cloud
Computer Vision
Deep Learning
DevOps
Docker
ETL
GCP
Google Cloud Platform
Kafka
Keras
Kubernetes
Machine Learning
NoSQL
Optimization
Pandas
PySpark
Python
PyTorch
Spark
SQL
Tensorflow
We are Data Nerds. Astronomer & Amazon Consulting Partners.
machine learning • data science • deep learning • artificial intelligence • consulting
51 - 200
• Project Management: Effectively manage projects by engaging with customers to understand the scope of work. • Team Leadership: Lead teams, collaborating with Machine Learning and data engineers. • Lead ML Model Productization: Champion the productization of ML models following MLops best practices, including orchestration, testing, monitoring, and serving, to benefit our clients. • ML POC Development: Collaborate with Machine Learning Engineers to develop meaningful ML Proof of Concepts (POCs) for internal and client requirements. • ML Model Lifecycle Management: Oversee the lifecycle of Machine Learning models, optimizing them when necessary to enhance performance, latency, memory, and throughput. • Business-Technical Translation: Translate business and mathematical/statistical requirements into software implementations, making informed trade-offs between time, quality, and client-specific needs. • Research and Innovation: Explore emerging ML Engineering technologies (Data Science, Data Engineering, DevOps) and techniques to enhance our toolset, best practices, and overall business value. • Project Strategy: Participate in defining project roadmaps, timelines, and estimates for new initiatives. • Knowledge Sharing: Document and disseminate industry-leading practices in AI/ML within the organization. • Technical Interviews: Collaborate on hiring interview processes (exam reviews and technical interviews)
• Demonstrated leadership skills and experience in client interactions. • Demonstrated work experience in roles such as Machine Learning Engineer, ML Architect or similar. • In-depth understanding of AI/ML principles, encompassing neural networks, supervised and unsupervised ML models, time series forecasting, and more. • Familiarity with Modern Data Architectures, including the implementation of Data Warehouses and Data Lakes, as well as DevOps tool/stack and methodologies (CI/CD, Kubernetes, Docker, gitops, etc.). • Previous involvement with data processing ETL and ML workflows, e.g., Airflow, MLflow, DBT. • Understanding of Deep Learning frameworks and technologies such as Keras, PyTorch, Tensorflow. • Strong grasp of Python programming language and proficiency in at least one other strongly typed language. • Knowledge of mathematical modeling and proficient statistical intuition. • Experience in implementing Machine Learning-based systems, including ML model lifecycle management, monitoring, and setting up MLOps pipelines from scratch. • Ability to develop implementation plans by weighing the pros and cons of different alternatives. • Solid command of the English language for writing technical documents, such as Design Documents. Nice to have skills: • Experience with the Modern Data Stack. • Hands-on experience with cloud-based AI services like AWS Sagemaker, AWS Textract, GCP Vertex AI, or similar. • Profound knowledge of software development methodologies. • A positive problem-solving attitude. • Previous experience in client-facing tech consultancy roles. • A track record of delivering high-quality solutions. • Certification in cloud platforms, such as AWS Machine Learning. • Familiarity with Python Data libraries like SQLAlchemy, Pandas, Polars, PySpark, Great Expectations, etc.
• Participate in compensated social events • Access quality coworking spaces • Get an additional week of vacation each year (Mutt Week) • We cover the costs of your Amazon Web Services (AWS) and Google Cloud Platform (GCP) certification exams and study materials • Enjoy a day off to celebrate your birthday • Improve your English language skills through in-company English lessons
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