Machine Learning Sr Software Engineer
Symantec Corporation (NASDAQ: SYMC) is the global leader in cyber security. Operating one of the world’s largest cyber intelligence networks, we see more threats, and protect more customers from the next generation of attacks. We help companies, governments and individuals secure their most important data wherever it lives.
About the Role:
Hawk is Symantec’s LifeLock Artificial Intelligence platform, that innovate itself and provides unique user experience in security space. It’s a cutting edge feature and a key component of Lifelock’s strategy. We are growing a team of Machine Learning engineers who love solving complex problems with data and are excited by the prospect of creating the security behind new Lifelock features. As a Machine Learning Engineer, you will be responsible for defining and building/implementing smart algorithms. You’ll be part of a team that is user-focused, has a mentality for experimentation, and iterates quickly.
Who you are:
- You have a strong foundation in Machine Learning and Computer Science. You have a broad understanding of state of the art in Machine Learning and Natural Language Processing.
- You have strong experience in data modeling and evaluation and have applied machine learning algorithms or libraries to solve a real world problem.
- You have experience building production services and/or models, preferably as part of a product development team. A track record of implementing data-driven products is ideal.
- You have deep understanding of complex data structures and time complexity.
- You have worked in a collaborative development environment and have experience with continuous integration and delivery.
- You can describe and speak in an approachable way about complex analyses and concepts within a cross-functional team. You are a great “analytic translator”.
- You are a proficient Python/Node programmer and have significant work experience with noSQL DB like Mongo.
- Functional/Technical Skills
- Learning on the Fly
- Time Management
- Peer Relationships
- Standing Alone
- Drive for Results
- Customer Focus
- Integrity and Trust
- Ability to protect all forms of highly confidential and proprietary business information and ability to maintain the highest standards of privacy and security.
- Ability to follow and abide by all information and security policies and practices.
Responsibilities and Duties
What you’ll do:
Define Machine Learning pipelines and Develop robust, scalable production Machine Learning products using Python/Tensorflow. You’ll evaluate trade-offs and do performance tuning for production traffic.
Innovate and iterate on Machine Learning algorithms in collaboration with Machine Learning Engineers and Software Engineers
Collect, process and cleanse data from a wide variety of sources. Transform and convert unstructured data set into structured data for algorithm input.
Evaluate the effectiveness of the algorithm and improvise it with model and/or data.
Qualifications and Skills
Bachelor’s degree in Computer Science or Information Systems.
Minimum 2 years in a Machine Learning engineering role with overall minimum experience of 8 years that includes-
Language/Platforms/Frameworks: Python, NodeJS, TensorFlow, scikit learn, NLTK, fasttext, OCR etc.
Application Design: Model-View-Controller (MVC), Object Oriented Programming, RESTful web services
Web Services/API integration: REST, SOAP
Working Unix experience
Knowledge of Deep learning – CNNs, RNNs,GANs is a plus
Excellent analytical, debugging skills and fast learner.
Solid understanding of version control systems such as Git and Subversion
Experience with gathering and documenting technical requirements and specifications
Experience using different development methodologies including Scrum, and/or Agile, and test-driven development.
Disciplined approach to software engineering best practices (e.g. unit testing, code reviews, design documentation, quality assurance)
M.S. or Ph.D in Computer Science is a plus.
A history of open-source contribution
Symantec is an equal opportunity employer. All candidates for employment will be considered without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, physical or mental disability, veteran status, or any other basis protected by applicable federal, state or local law.