Senior Machine Learning Software Engineer Jobs

Be comfortable working in a fully-remote environment

Experience designing, training, and evaluating supervised and unsupervised models using popular ML frameworks

Working knowledge of deep learning and clustering algorithms

Experience with writing and running tests (unit tests, integration tests, regression tests)

Experience with performing data analysis as required to support data quality decisions

Experience with AWS or GCP

Using your technical acumen and tools like OpenAI Code Interpreter, LangChain, and AWS Glue to revolutionize our educational services.

Enough coding experience to assemble a set of prompts into a working prototype service in a single day

Experience working with CodeInterpreter, LangChain, AWS Glue, and AI Orchestration tools to create 100% AI-based workflows

Prior successful experience automating manual processes

Senior Machine Learning Engineer key responsibilities

Rolling up your sleeves, evaluating outputs, building prototypes, and doing whatever it takes to push the quality bar higher.

Present model capabilities and output to senior leadership

5+ years of experience as back-end software engineer

3+ years of experience in productionizing machine learning (ML) systems

Hands-on experience of deploying ML models/systems to cloud infrastructure

Experience with one of the Infrastructure as Code tools (Terraform, AWS CDK, etc)

Make a difference in the lives of thousands of students as they explore educational opportunities

Experience using SQL/NoSQL and knowledge in database management.

3+ years of relevant industry experience with developing machine learning models.

Detailed knowledge of advanced statistics, probability, and of supervised, semi/self-supervised and unsupervised learning.

Experience in designing end-to-end machine learning systems

Demonstrated knowledge of algorithms and data structures

Previous experience as a Tech Lead or experience in a similar role.

8+ years of experience in product management, with 2+ years of experience with automation experience

Define product requirements and manage delivery of core workflows for automation and machine learning

Engage with stakeholders and actors utilizing current systems to gather requirements and drive adoption of future state products

Intake, prioritize and manage the backlog for multiple products and stakeholders

Manage working relationships across multiple liquidity engineering and product teams that rely on this platform to deliver for our customers

Lead the full cycle of product development and rollout — from requirements gathering and prioritization, to design and oversight of implementation

Excellent English communication skills, both verbal and written

Programming experience with at least one object-oriented language (bonus for C#) or scientific language (bonus for Python)

Interest or experience in hydrology or environmental sciences

Must be currently enrolled in an accredited post-secondary institution

You are passionate about data science and full-stack software engineering

Keen to learn about software engineering and technology; incessantly inquisitive

5+ years experience with applied Machine Learning or Deep Learning

An appreciation for the connection between the software you build and the experience it delivers to customers

Paid Life insurance, AD&D, and disability benefits

Python (NumPy, Pandas, sklearn, xgboost, TensorFlow, keras, etc.)

MySQL, Snowflake, GCP/AWS and Tableau

A graduate degree in Computer Science, AI, ML, Applied Math, Stats, Physics, or a related technical field

Leverage exceptional mathematical skills to perform computations and work with the algorithms involved in machine learning programming.

Previous experience in machine learning and developing AI products.

Exceptional mathematical skills to perform computations and work with algorithms.

Excellent written and verbal communication skills, with the ability to explain complex processes to non-technical stakeholders.

Strong analytical skills and attention to detail.

Strong knowledge of statistical analysis and data modeling techniques.

Identify opportunities to enhance ad measurement capabilities by diving deep into our platform and understanding the needs of our advertisers.

2+ years of experience with applied machine learning models and large-scale ML systems

3+ years of end-to-end experience of training, evaluating, testing, and deploying machine learning models

Experience of orchestrating complicated data pipelines and system engineering on large-scale dataset

Prior experience with Ads/Ads Measurement is a plus

Workspace benefits for your home office

Advanced knowledge and hands-on experience with NLP or CV

Minimum 3 years of professional experience building and implementing production-scale Machine Learning models

Extensive experience with machine learning libraries (Numpy, Pandas, SciKit Learn, XGB, etc.) for both supervised and unsupervised learning

Hands-on experience writing production ML code in Python and SQL

Excellent communication skills for effective collaboration with product, operations, and DevOps teams

Experience with backend software development

Define the processes needed to achieve and sustain operational excellence including security, cost management, tuning and ongoing optimizations

Partnering with analytics, project management and business leadership to implement the optimal solutions

Collaborate with cross-functional teams - business stakeholders, engineers, program management, project management, etc. - to produce the best solutions possible

Experienced programmer with expert level programming skills, required tuning and debugging

Knowledge of Data Visualization and Exploratory data analysis skills ( Power BI or similar )

Experience working with data, Azure cloud and MLOps

2+ years of experience building and maintaining containerized runtime environments for Data Science and Machine Learning (e.g. PyTorch, TensorFlow)

2+ years of experience with Unix-based systems

2+ years of experience building automated CI/CD pipelines for containers

2+ years of experience in Python programming for Machine Learning and/or application development

1+ years of experience building and maintaining containerized runtime environments supporting GPUs (e.g. CUDA)

Prior experience in building containerized runtime environments and frameworks such as Jax, TensorRT, Onnx, DeepSpeed and Horovod

Strong programming skills in Python and experience with machine learning libraries such as TensorFlow, PyTorch, or Scikit-Learn

Develop and implement machine learning models and algorithms that meet business needs and requirements

Manage end-to-end machine learning pipelines, from data preprocessing to model training and deployment

6 years of overall development experience

At least 2+ years of experience in machine learning and AI software development

Experience with cloud platforms such as AWS, GCP, or Azure and their machine-learning services

Define and apply state of the art software engineering practices and tools (configuration management, static analysis, unit tests and beyond).

Network in the company and actively distribute your knowledge and expertise

Bachelors degree or equivalent industrial experience in Computer Science, Software Engineering, Electrical Engineering or any related field.

Experience in implementing scalable software for Machine Learning applications, preferably in High Performance Computing (HPC) and/or cloud platforms.

Experience with Machine Learning Stacks (e.g. MLflow, Kubeflow, Seldon Core etc.).

Experience that demonstrates your team-oriented, innovative, and strategic working styles

Demonstrated experience of HCI and/or Ubiquitous Computing research fundamentals, including experience designing and evaluating novel technologies

Excellent written and oral communication skills

Understand product demands and industry technology trends to define research directions

Perform interaction design, core algorithm development, prototype development, user experimentation and collaborate with product teams to implement research findings into products

Generate intellectual property such as patents and trade secrets based on research outcomes

Publish papers in peer-reviewed scientific journals/conferences

Bachelor’s degree or equivalent practical experience.

5 years of experience with software development in one or more programming languages, and with data structures/algorithms.

3 years of experience testing, maintaining and/or launching software products, and 1 year of experience with software design and architecture.

3 years of experience with ML/AI algorithms and tools, deep learning and/or natural language processing.

1 year of experience in a technical leadership role. Experience developing accessible technologies.

Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.

Minimum 5 years relevant work experience (including internships).

Identifies strategic information needs of internal clients and translates these into data requirements to build high performance data stores.

Experience with Data Science and supporting data scientists to get their models successfully deployed to production.

Extensive knowledge of deployment tools such as AWS, Google Cloud, Azure, Docker, Flask, MLFlow, and Airflow.

Master's degree in Computer Science, Technology, or Engineering preferred.

Proven track record in the application of ML/NLP/Search Engine/Big Data.

BS or MS in Computer Science/Software Engineering or equivalent work experience.

Experience with support of AI/ML Solutions in Production Systems

Experience developing end to end expertise of a complex system using multiple technologies

You have strong software engineering skills and strong programming skills in Python/Pandas/ML Libs

Experience with the use of Kubernetes at scale

You have working experience with Docker, and big data frameworks.

Over five years of experience building software applications in large scale distributed systems.

Experience with building and maintaining high availability, low latency systems, especially with respect to reliability, testing, and observability.

Over 2 years of experience supporting Machine Learning Infrastructure.

Experience optimizing the end-to-end performance of distributed systems.

Experience training and shipping machine learning models to production to solve critical business problems.

Building powerful, flexible, and user-friendly infrastructure that powers all of ML at Stripe.

BS, MS, or PhD in Computer Science, Mathematics, Statistics, or other quantitative fields or related work experience

10+ years of engineering experience with 6+ years building Machine Learning or AI systems

Experience working in a start-up or in a start-up like environment

Strong industry experience working with large scale data systems

Strong analytical and problem-solving skills

Proven software engineering skills across multiple languages including but not limited to Python