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About Traceable
Join the future of API security with a company founded by serial innovators reshaping the software industry. Visionaries Jyoti Bansal and Sanjay Nagaraj, creators of AppDynamics (acquired by Cisco for $3.7B), established Traceable with a bold ambition: to become the global leader in API security.
We're experiencing explosive growth, tripling revenue and scaling rapidly to empower enterprises facing evolving API threats. This success is fueled by a winning strategy: unwavering customer obsession, relentless product innovation, and strategic partnerships – all backed by the entrepreneurial expertise behind past industry-defining success. Our cutting-edge solution makes API security manageable for businesses across the globe, ensuring APIs drive growth, not risk.
Join this winning team and make your mark!
About the Role
As part of the growing team at Traceable, you will work with an amazing group of data scientists and data platform engineers to build all things next gen application security. You’ll be expected to help conceptualize, code, and deploy data science models at scale using the latest technologies & tools. Key skills include data wrangling, feature engineering, developing ML pipelines and evaluation metrics.
- Data prep for machine learning models (discovering data sources, accessing data, transforming data and cleaning data)
- Work with data scientists on building ML pipelines and productionsize them
- Partner with data scientists to understand, implement, refine and design machine learning algorithms and ML pipelines. Iterating and failing fast is critical.
- Run regular A/B tests, gather results, perform statistical analysis, draw conclusions on the impact of your models.
- Work cross functionally with product managers, data scientists and product engineers, and communicate results to peers and leaders.
- Explore latest innovations and developments around Machine Learning Platforms and open source frameworks, evaluate them and help in adoption
Qualifications:
- MS or PhD degree in Computer Science, ML or related field.
- Minimum 5 years of relevant industry experience.
- Programming languages, frameworks and tools :
- Strong skills: Python, Spark, Java, Kafka/Kafka Stream, Kubernetes
- Good to have: Airflow(or equivalent orchestration frameworks), Deep Learning, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R
- Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering).
- Knowledge of common data query and data processing tools (i.e. SQL)
- Good computer science fundamentals - data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning).
- Experience of building, deploying and operating ML pipelines at massive scale using batch and streaming big data technologies in Kubernetes.
- Experience of working on anomaly detection, security products and fraud detection will be a plus
- Experience on the tooling of python applications will be a plus
We value diversity and treatment of employees and applicants is based on merit, talent and qualification. We encourage people from underrepresented groups to apply. We believe the key to success is bringing together unique perspectives and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Direct applicants only. Recruiting agencies: Please do not email or call our team. We are not accepting agency candidates.
We believe the key to success is bringing together unique perspectives and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
For qualified US: applicants with criminal histories, consideration will be consistent with the requirements of the San Francisco Fair Chance Ordinance. All your information will be kept confidential according to EEO guidelines.
