Sr Machine Learning Software Engineer

Key Skills

Agile methodologies, Algorithms, Apache Airflow, Apache Flink, Apache Hadoop, Apache Kafka, AWS, AWS Kinesis, C++, Cloud computing, Computer Vision (CV), Continuous Integration & Continuous Delivery - CI/CD, Data Visualization, Docker, Kubernetes-K8s, Machine learning techniques, MLOps tools, MxNet, Natural Language Processing (NLP), NumPy, Pandas, Presto, Python Programming, PyTorch, Scikit-learn, SciPy, Spark Core, TensorFlow

Job Description

Our Mission

Our mission is to solve the most important and fundamental challenges in AI and Robotics to enable future generations of intelligent machines that will help us all live better lives

Software Engineers will work cross-functionally, creating new technology to improve software development for robots. If you have a passion for developing technology for robots and use it to advance their capabilities and usefulness, you will want to join us! We are onsite in our new Cambridge, MA office where we are building a collaborative and exciting new organization.

Responsibilities

• Train, deploy and maintain various ML algorithms on cloud and on-premise infrastructure
• Develop process, pipeline and tools for all components of ML lifecycle (training, evaluation, deployment)
• Build and maintain data, model and experimentation pipelinesHelp with model tuning, algorithm selection, hyperparameter search using our MLops platform
• Partner closely with research and applied science teams to put models into production
• Promote quality and reliability through regular code reviews

Requirements

• 10+ years overall experience delivering robust code that includes 5 years with ML
• BS or MS in computer science, engineering, data science, or related technical, math, or scientific field
• Experience with C++ or Python
• Experience with deep-learning techniques in NLP and Computer Vision
• Experience using data science tools, libraries, and frameworks (e.g. Scikit-learn, caret, mlr, mllib, SparkML, NumPy, SciPy, Pandas, TensorFlow, PyTorch, MXNet)
• Experience with git, issue tracking, CI/CD, and modern software engineering practices
• Understanding of machine learning algorithms such as Linear and Logistic regressions, Decision tree, Naive Bayes, KNN, K-means, Random forest

Bonus (Not Required)

• Experience with Docker, Kubernetes, cloud computing, or similar applications
• Experience with data processing, logging, and visualization tools
• Experience with MLOps (model versioning, model and data lineage, monitoring, model hosting and deployment, scalability, orchestration, continuous learning)Experience creating orchestration workflows with tools such as Airflow, Kubeflow, or AWS Step Functions
• DevOps experience (e.g. CI/CD Pipelines, Infrastructure as Code, containers, Agile software development)
• Experience implementing IoT solutions such as edge computing
• Big Data batch and real time data processing experience (e.g. Hadoop, Spark , Presto, Kafka, Kinesis, Flink)

We provide equal employment opportunities to all employees and applicants for employment and prohibit discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws