Apply

Engineering Manager, Machine Learning

Posted over 1 year agoViewed

View full description

📍 Location: Remote - us

💸 Salary: {180000,210000}

🔍 Industry: Ai technology

🗣️ Languages: English

Requirements:
Deep understanding of machine learning concepts and techniques, data science experience, strong technical and software development skills, excellent communication and collaboration skills, management experience, strategic mindset, proficiency in python and machine learning frameworks.
Responsibilities:
Leading a team of ml engineers and data scientists, developing and deploying machine learning models, managing multiple machine learning projects, collaborating with other departments, communicating technical concepts to non-technical stakeholders, hiring and recruiting top talent.Apply

Related Jobs

Apply

📍 United States

🔍 Go-to-market solution for revenue teams

🏢 Company: Apollo.io👥 501-1000💰 $100,000,000 Series D over 1 year agoSoftware Development

  • 3-5 years' experience in people management, preferably leading senior engineers and staff engineers.
  • 6+ years of experience building Machine Learning or AI systems.
  • Experience deploying and managing machine learning models in the cloud.
  • Strong analytical and problem-solving skills.
  • Proven software engineering skills in production environment, primarily using Python.
  • Experience with Machine Learning software tools and libraries (e.g., Scikit-learn, TensorFlow, Keras, PyTorch, etc.).
  • Preferred: Experience with Databricks, Google Cloud Platform, Snowflake, mlflow, and Airflow.
  • Experience with Large Language Models (LLMs) or similar technologies.
  • Experience with one or more of the following: natural language processing, deep learning, recommendation systems, search relevance & ranking, and speech-to-text conversion.

  • Help the Machine Learning team define, set, and adhere to goals and expectations.
  • Drive a culture around excellence, learning, and fun.
  • Critically observe and improve development and management processes within Apollo engineering.
  • Work closely with key stakeholders such as the CTO, Product Managers, and Designers to deliver high quality Machine Learning products (like lead scoring, recommendations, LLM based products, AI agents, etc.) at a rapid pace for an ever-increasing user base.
  • Change, and be a part of key decision-making processes within the engineering organization.
  • Participation in key technical decision-making discussions such as sprint planning, software design, and occasionally code reviews.
  • Help build and scale a world-class engineering team by sourcing and hiring candidates.
  • Hold systematic weekly 1:1 touch points with engineers to deliver and receive quality feedback.
  • Work with engineers to develop and execute on personalized goals.
  • Conduct objective and helpful quarterly performance reviews for engineers.

LeadershipPythonKerasMachine LearningMLFlowPeople ManagementPyTorchSnowflakeAirflowTensorflowCollaboration

Posted 2 months ago
Apply
Apply

🧭 Full-Time

🔍 Go-to-market solutions for revenue teams

🏢 Company: Apollo.io👥 501-1000💰 $100,000,000 Series D over 1 year agoSoftware Development

  • 3-5 years' experience in people management, preferably leading senior engineers and staff engineers.
  • 6+ years of experience building Machine Learning or AI systems.
  • Experience deploying and managing machine learning models in the cloud.
  • Strong analytical and problem-solving skills.
  • Proven software engineering skills in production environment, primarily using Python.
  • Experience with Machine Learning software tools and libraries (e.g., Scikit-learn, TensorFlow, Keras, PyTorch).
  • Preferred: Experience with Databricks, Google Cloud Platform, Snowflake, mlflow, and Airflow.
  • Experience with Large Language Models (LLMs) or similar technologies.
  • Experience with one or more of the following: natural language processing, deep learning, recommendation systems, search relevance & ranking, and speech-to-text conversion.

  • Help the Machine Learning team define, set, and adhere to goals and expectations.
  • Drive a culture around excellence, learning, and fun.
  • Critically observe and improve development and management processes within Apollo engineering.
  • Work closely with key stakeholders such as the CTO, Product Managers, and Designers to deliver high quality Machine Learning products.
  • Participate in key technical decision-making discussions such as sprint planning and software design.
  • Help build and scale a world-class engineering team by sourcing and hiring candidates.
  • Hold systematic weekly 1:1 touch points with engineers to deliver and receive quality feedback.
  • Work with engineers to develop and execute on personalized goals.
  • Conduct objective and helpful quarterly performance reviews for engineers.

LeadershipPythonKerasMachine LearningMLFlowPeople ManagementPyTorchSnowflakeAirflowTensorflow

Posted 4 months ago
Apply

Related Articles

Posted 4 months ago

Insights into the evolving landscape of remote work in 2024 reveal the importance of certifications and continuous learning. This article breaks down emerging trends, sought-after certifications, and provides practical solutions for enhancing your employability and expertise. What skills will be essential for remote job seekers, and how can you navigate this dynamic market to secure your dream role?

Posted 4 months ago

Explore the challenges and strategies of maintaining work-life balance while working remotely. Learn about unique aspects of remote work, associated challenges, historical context, and effective strategies to separate work and personal life.

Posted 4 months ago

Google is gearing up to expand its remote job listings, promising more opportunities across various departments and regions. Find out how this move can benefit job seekers and impact the market.

Posted 4 months ago

Learn about the importance of pre-onboarding preparation for remote employees, including checklist creation, documentation, tools and equipment setup, communication plans, and feedback strategies. Discover how proactive pre-onboarding can enhance job performance, increase retention rates, and foster a sense of belonging from day one.

Posted 4 months ago

The article explores the current statistics for remote work in 2024, covering the percentage of the global workforce working remotely, growth trends, popular industries and job roles, geographic distribution of remote workers, demographic trends, work models comparison, job satisfaction, and productivity insights.