Apply

Machine Learning Engineer

Posted 3 months agoViewed

View full description

πŸ’Ž Seniority level: Senior, 5+ years

πŸ” Industry: DefenseTech

🏒 Company: TurbineOneπŸ‘₯ 11-50πŸ’° $15,000,000 Series A 10 months agoSecurityPublic Safety

πŸ—£οΈ Languages: English

⏳ Experience: 5+ years

Requirements:
  • High standard of ethics, grit, integrity and moral character.
  • 5+ years of work experience in moving ideas from experimental to production systems.
  • Proficiency in writing documents detailing experimental results and solutions.
  • Strong software engineering skills with experience in maintainable complex systems.
  • College degree in Computer Science or Machine Learning.
  • Extensive knowledge of deep learning algorithms.
  • Experience in creating and training models in TensorFlow, PyTorch, Jax.
  • Experience in optimizing data pipelines and normalization techniques.
Responsibilities:
  • Solve product challenges from prototype to customer delivery.
  • Iterate with engineering and product teams for feedback.
  • Ideate on ML systems under resource constraints.
  • Create production-grade ML systems for field deployment.
  • Design API for integrating third-party ML solutions.
  • Develop infrastructure for custom ground-truth datasets.
  • Maintain cloud-based systems for quality testing.
  • Develop testing frameworks for ML components.
  • Stay updated on AI/ML techniques and share knowledge.
Apply

Related Jobs

Apply

🧭 Full-Time

πŸ” Artificial Intelligence, Machine Learning

🏒 Company: OfferFitπŸ‘₯ 51-100πŸ’° $25,000,000 Series B about 1 year agoArtificial Intelligence (AI)Machine LearningMarketing Automation

  • 2+ years of experience working with Python in a product setting, including 1+ years in the data/machine learning ecosystem.
  • Experience working with at least one major cloud platform (GCP, AWS, Azure, etc.).
  • Experience putting ML models into production.
  • General understanding of supervised learning principles is a plus but not required.
  • Must be fluent in English, both written and verbal.

  • Use robust software engineering best practices to design, implement, and improve modular components in a cutting-edge ML product.
  • Work closely with OfferFit customers to understand, translate and generalize particular use cases to generic platform components.
  • Apply extensive knowledge of Python to produce clean, readable, and extendible code, and coach team members.
  • Collaborate with teams responsible for OfferFit’s product strategy and roadmap.
  • Support teams implementing OfferFit for customers to ensure their success.
Posted 3 days ago
Apply
Apply

πŸ“ Argentina

🧭 Full-Time

πŸ” Data Intelligence

🏒 Company: Netrix GlobalπŸ‘₯ 501-1000InternetInformation TechnologyTelecommunications

  • Proven experience as a Machine Learning Engineer or in Data Science roles, with strong skills in data pipelines and Machine Learning model development.
  • Experience working in cloud environments (AWS) for at least 2 years.
  • Solid proficiency in Python and machine learning libraries such as TensorFlow, PyTorch, or similar.
  • Advanced English level.
  • Experience using SageMaker and other AWS data services: S3, AWS Glue, Athena.
  • Experience with Generative AI models and deploying them in production.
  • Proficiency in DevOps tools (Git, pipelines) and infrastructure as code (Terraform, CloudFormation).
  • Ability to work in Agile teams under Scrum methodology.

  • Design, build, and optimize data workflows for Machine Learning and GenAI solutions in cloud environments.
  • Develop and deploy Machine Learning and Generative AI (GenAI) models using AWS SageMaker.
  • Create and manage data and model pipelines to improve the efficiency of AI and machine learning systems.
  • Prepare and structure data for advanced AI and GenAI solutions.
  • Ensure seamless integration of data and AI solutions within cloud architectures, including data security and governance aspects.
  • Document and rigorously test models and workflows to meet accuracy and performance requirements.
  • Monitor and enhance the performance of Machine Learning models and services in production.
  • Manage Data Lake architectures, tailoring data to the needs of Machine Learning and GenAI workloads.

AWSPythonCloud ComputingMachine LearningPyTorchTensorflowDevOpsTerraform

Posted 3 days ago
Apply
Apply

🧭 Full-Time

πŸ” Healthcare technology

🏒 Company: Redesign Health

  • Graduate degree or equivalent in Computer Science, Applied Mathematics, or related field from an IIT or top global university.
  • 6+ years in a senior technical role at a major venture-backed startup.
  • Outstanding executive communicative presence.
  • Proficient in at least one modern programming language, particularly Python.
  • Expertise in working with LLMs and building complex workflows.
  • Familiarity with modern data stack technologies, including AWS, Docker, and machine learning frameworks.

  • Originate, lead, and deliver on critical, 0-to-1 AI projects across the company.
  • Design and build AI-powered technologies to enhance the venture-building process.
  • Deliver technical value through projects involving deep health domain research and founder sourcing.
  • Experiment with proof of concepts and evaluate solutions based on informed insights.
Posted 3 days ago
Apply
Apply

🧭 Full-Time

πŸ’Έ 190000.0 - 230000.0 USD per year

πŸ” Health and wellness

🏒 Company: hims & hers

  • 10+ years working in Engineering or as a Machine Learning Engineer with proven experience.
  • Expertise in modern machine learning orchestration and deployment tools such as Databricks MLFlow, AWS SageMaker, and Metaflow.
  • Proficiency in Python and machine learning libraries (e.g., PyTorch, Scikit-learn, Tensorflow).
  • Strong understanding of MLOps principles with experience in automating workflows for model training, deployment, and monitoring.
  • Familiarity with machine learning fundamentals, statistical modeling techniques, and data preprocessing pipelines.
  • Experience with LLM deployment tooling is a plus.
  • Hold a Master's degree in Computer Science or related fields.
  • Possess a collaborative mindset and excellent communication skills.

  • Collaborate with ML engineers, data scientists, product managers, and other engineering teams.
  • Build, deploy, and scale machine learning-based systems.
  • Ensure reliability and performance in production.
  • Guide and make technical decisions regarding productionizing data science and ML models.
  • Evaluate and implement state-of-the-art tools and frameworks.
  • Mentor and be mentored by other engineers.
  • Actively participate in retrospectives to drive continuous process and culture improvement.
Posted 3 days ago
Apply
Apply

πŸ“ United States

🧭 Full-Time

πŸ’Έ 185800.0 - 322000.0 USD per year

πŸ” Technology, Internet Services

🏒 Company: RedditπŸ‘₯ 1001-5000πŸ’° $410,000,000 Series F over 3 years agoπŸ«‚ Last layoff over 1 year agoNewsContentSocial NetworkSocial Media

  • 3-10+ years of industry experience as a machine learning engineer or software engineer developing backend/infrastructure at scale.
  • Experience building machine learning models using PyTorch or Tensorflow.
  • Experience with search & recommender systems and pipelines.
  • Production-quality code experience with testing, evaluation, and monitoring using Python and Golang.
  • Familiarity with GraphQL, REST, HTTP, Thrift, or gRPC and design of APIs.
  • Experience developing applications with large scale data stacks such as Kubeflow, Airflow, BigQuery, Kafka, Redis.

  • Develop and enhance Search Retrievals and Ranking models.
  • Design and build pipelines and algorithms for user answers.
  • Collaborate with product managers, data scientists, and platform engineers.
  • Develop and test new pipeline components and deploy ML models.
  • Ensure high uptime and low latency for search systems.

GraphQLPythonKafkaKubeflowMachine LearningPyTorchAirflowRedisTensorflow

Posted 4 days ago
Apply
Apply

πŸ“ Kenya, the Philippines, Mexico, India, USA

πŸ” Fintech

NOT STATED

  • Build and maintain Tala’s core machine learning and causal inference services.
  • Own customer-facing real-time streaming feature extraction and model inference.
  • Manage model-related batch compute platforms and jobs.
  • Define and measure service level objectives.
  • Conduct root cause analysis and software/architecture design.
  • Assess technical maturity and provide mentorship.

AWSDockerPythonSQLKafkaMachine LearningPyTorchSoftware ArchitectureData engineeringTensorflowCI/CD

Posted 5 days ago
Apply
Apply

πŸ“ Australia

πŸ” AI

  • Strong experience with MLOps pipelines using Kubeflow, MLflow, or similar.
  • Proficiency in Python for maintainable code.
  • Hands-on experience with AWS services like S3, EC2, and SageMaker.
  • Deep understanding of container orchestration tools like Kubernetes.
  • Experience designing scalable ETL pipelines with SQL and NoSQL databases.

  • Design, build, and maintain MLOps pipelines for machine learning model lifecycle.
  • Collaborate with DevOps teams for cloud infrastructure management, focusing on AWS.
  • Implement CI/CD pipelines for smooth transitions from research to production.
  • Design scalable data pipelines for data collection and processing.
  • Deploy and monitor machine learning models in production.

AWSDockerPythonSQLETLKubeflowKubernetesMLFlowGrafanaPrometheusNosqlCI/CDTerraform

Posted 8 days ago
Apply
Apply

🧭 Full-Time

πŸ” Data and technology

  • 5+ years of experience in machine learning.
  • Deep experience with current-generation ML algorithms and frameworks (e.g., XGBoost, PyTorch, TensorFlow).
  • Hands-on expertise with generative AI (e.g., fine-tuning GPT, reinforcement learning).
  • Programming skills in Python (e.g., Pandas, NumPy, PyTorch, LlamaIndex, Langchain, Haystack).
  • Experience with cloud platforms like AWS SageMaker, Databricks, GCP, Snowflake, or Azure.
  • Experience in building and maintaining large-scale ML systems in production, including data pipelines and orchestration tools (e.g., Kubernetes, Jenkins).
  • Experience with asynchronous REST API development, cloud infrastructure, and DevOps practices.
  • Familiarity with testing, troubleshooting, and triaging production issues.
  • Domain expertise in financial services, credit modeling, or healthcare analytics is a plus.

  • Develop and operationalize machine learning models by designing, building, and deploying scalable ML frameworks and pipelines.
  • Lead the development of custom models, including LLMs and traditional ML algorithms for applications such as credit risk, fraud detection, and customer insights.
  • Shape Experian's AI Platform by overseeing the creation of tools for training, fine-tuning, and deploying models, including generative AI applications.
  • Ensure robust system architecture for managing high-volume data and model evaluations.
  • Mentor a diverse team and work with stakeholders to align technical solutions with business goals.
  • Handle challenges related to model bias, fairness, and explainability while establishing best practices for development.
Posted 8 days ago
Apply
Apply

πŸ“ France

🧭 Internship

πŸ” Machine Learning / AI

🏒 Company: Hugging FaceπŸ‘₯ 51-200πŸ’° $235,000,000 Series D over 1 year agoSoftware Development

  • Experience using modern deep learning libraries and LLM APIs.
  • Understanding tradeoffs between different models and APIs.
  • Knowledge of how to fine-tune LLMs.
  • Ability to create retrieval-augmented generation pipelines.
  • Experience with re-rankers for two-stage retrieval.
  • Comfortable exploring and contributing to a codebase in Python and Svelte-flavored JavaScript.
  • Possess a 'product mindset' for experimenting with user interfaces.

  • Expand the effort to develop AI tools for Gradio.
  • Leverage ~500k Gradio spaces and user prompts to create a sophisticated model pipeline.
  • Help developers understand and write Gradio code effectively.

PythonMachine Learning

Posted 9 days ago
Apply
Apply

πŸ“ United States

🧭 Full-Time

πŸ’Έ 100000.0 - 125000.0 USD per year

πŸ” B2B SaaS

🏒 Company: DocumoπŸ‘₯ 51-100πŸ’° $4,999,999 8 months agoProductivity ToolsDocument ManagementEnterprise SoftwareHealth CareSoftware

  • Experience with the software development life cycle (SDLC).
  • Knowledge in performance optimization and debugging of ML models.
  • Ability to work with data processing, model versioning, and experiment tracking.
  • Experience in collaborating with cross-functional teams.
  • Ability to provide technical support and resolve escalated issues.

  • Design, develop, and maintain ML pipelines and systems.
  • Implement and optimize model fine-tuning processes.
  • Develop and maintain infrastructure for model deployment and monitoring.
  • Collaborate with product management to ensure ML solutions meet customer needs.
  • Lead code reviews and maintain best practices for ML model deployment.
  • Mentor junior engineers and share expertise in ML engineering.

AWSDockerPythonData AnalysisData MiningMachine LearningMLFlowPyTorchAlgorithmsTensorflow

Posted 10 days ago
Apply

Related Articles

Posted 5 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 5 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 5 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 5 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 5 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.