Senior Machine Learning Engineer

Posted 6 days agoViewed

💎 Seniority level: Senior, 3+ years

📍 Location: Germany, India

🔍 Industry: Customer relationship management (CRM) software

🏢 Company: HubSpot👥 1001-5000💰 $35,000,000 Series E about 12 years ago🫂 Last layoff 12 months agoSaaS Analytics Marketing Copywriting Social Media

🗣️ Languages: English

⏳ Experience: 3+ years

🪄 Skills: DockerPythonSQLData AnalysisKafkaKubernetesMachine LearningPyTorchSnowflakeTensorflowCI/CD

Degree in computer science, statistics, applied mathematics, economics, or other quantitative discipline.
3+ years experience in machine learning with multiple models deployed in operational settings.
Expert knowledge of machine learning/AI techniques.
Strong familiarity with Python programming and ML frameworks (Scikit-learn, TensorFlow, PyTorch, HuggingFace).
Familiarity with CI/CD systems (GitHub Actions, Jenkins, CircleCI).
Familiarity with monitoring & alerting systems (DataDog, Monte Carlo, Cloudwatch).
Familiarity with Snowflake, SQL, DBT, and jinja templating.
Familiarity with standard ML deployment stack (Docker, Kubernetes, Spark, dask).
Ability to manage a software project from planning to maintenance.
Ability to communicate technical concepts to business leaders.
Creative and collaborative problem solver.

Build, train, evaluate, and deploy ML models and generative AI solutions at scale.
Work with complex datasets to extract relevant features and insights.
Conduct experiments and evaluations of ML models, using statistical methods and visualization tools.
Train and fine-tune large language models for tailored use cases.
Build strong relationships with internal stakeholders and understand their business problems.
Stay current with AI/ML trends and contribute to algorithm development.
Participate in code reviews, testing, and documentation activities.
Mentor junior ML Engineers and Data Scientists.

Posted 4 months ago

📍 US, UK, Germany, Australia

🔍 Employee experience platform

Python software engineering expertise.
Familiarity with various stages of the ML lifecycle and MLOps: data labeling, fine tuning models, evaluation, CI/CD, deployment, versioning, monitoring, etc.
Familiarity with machine learning libraries (e.g., TensorFlow, PyTorch, HuggingFace).
Understanding of transformer architectures and LLMs.
Experience working with AI, machine learning, LLMs and NLP.
Experience working with cloud platforms and infrastructure (e.g. AWS, GCP).

Participate in code reviews, architecture discussions, and contribute to best practices in ML engineering.
Collaborate and work closely with other engineers in your team through pair/mob programming, writing solution designs, or giving feedback on pull requests, to build shared understanding of your work.
Stay up-to-date with the latest advancements in machine learning and AI technologies and integrate them into our products.
Play a crucial role in delivering team objectives with other engineers in the team.

AWSPythonAgileGCPMachine LearningPyTorchTensorflowCI/CD

Posted 4 months ago

Posted 5 months ago

📍 Canada, UK, India

🔍 Technology, Machine Learning

Experience in a high growth agile software development environment.
Experience developing machine learning-driven applications.
Interest in statistical modeling and machine learning.
Good understanding of ETL, data warehousing, data modeling and data architecting.
Knowledge to work with data scientists and translate proof of concept models into production strength systems.
Development skills in Python, relational databases like MySQL or PostgreSQL, NoSQL databases such as Redis or Cassandra.
Experience with data processing frameworks like Spark or Presto and deep learning frameworks like TensorFlow or Pytorch.
Experience with microservice architectures.
Strong test automation skills (unit and functional).

Working closely with Product Managers, Architects and Data Scientists to design, build, maintain and optimize our data management and machine learning applications.
Develop software to deliver and integrate machine learning product capabilities into our platform through REST services.
Build data processing pipelines supporting data analysis and machine learning tasks, and automate data pipelines in production.
Perform code reviews and add automated testing to ensure software quality is high.
Collaborate with team members leveraging state of the art technologies in Python, ML/DL/NLP and cloud.

AWSDockerPostgreSQLPythonSoftware DevelopmentAgileData AnalysisETLKubernetesMachine LearningMySQLPyTorchCassandraRedisNosqlSparkTensorflowCI/CD

Posted 5 months ago

🔧 Requirements