Sales & Marketing | Job ID: 4-2020

About Sensai

Sensai is on a mission to develop the best Real-Time AI powered anomaly prediction tool for data centers & Cloud solutions as an essential element in the data center automation process & SLA monitoring.

If you enjoy working in a startup but want to sell a product with a huge community of customers globally come help us sell the next generation of intelligent, automated monitoring & troubleshooting tools.

At Sensai, we are committed to our work, customers, having fun and most meaningfully to each other’s success.

Responsibilities

The ML team leader’s job is to design and develop the cognitive core (encompassing multiple models) of a software based active monitoring tool which monitors, analyses and predicts behaviors in a Hybrid Cloud environment, taking it from concept to launch.

Lead, collaborate and work efficiently amongst a team of developers, designers and consultants. Work very closely with the system infrastructure and UI teams to build AI based projects from start to finish. The candidate is expected to know and adapt to leading technologies and to work hands-on. The ML team leader is expected to provide leadership to the ML team to develop efficient code and to create infrastructure to support team’s algorithmic development goals.

We are looking for someone who is passionate about problem-solving, has proven experience developing ML models in production at scale, a strong theoretical background, and proven experience leading data science teams.

Skills and Qualifications

• MS.C or Phd. in Computer Science, computer Engineering, Mathematics, Statistics, other technical sciences.
• 5+ years of experience ML production grade software – MUST
• At least 3 years’ experience as an ML project/team leader
• Strong theoretical and practical background in a variety of machine learning techniques, including unsupervised learning.
• Knowledge in causality – Advantage.
• Knowledge of ML system design, and with ML main algorithms.
• Experience in a fast-paced development environment, and an ability to execute against aggressive timelines.
• Highly creative and inquisitive; able to multitask effectively; embraces challenges and is a true team player.
• Working with Python, Java, TensorFlow.

Advantage

• Knowledge with big data, NoSQL, Elastic search, Spark
• Experience in startup environment
• Hybrid Cloud industry experience
• Networking experience

R&D | Full Time | Job ID: 2-2020

About Sensai

Sensai is on a mission to develop the best Real-Time AI powered anomaly prediction tool for data centers & Cloud solutions as an essential element in the data center automation process & SLA monitoring.

As a Senior Software Engineer at Sensai you will join the Infrastructure team, envision, build, deploy and develop a breakthrough AI driven Data Center Monitoring Platform with a new innovative approach.

At Sensai, we are committed to our work, customers, having fun and most meaningfully to each other’s success.

Responsibility

• Executing projects end-to-end from requirements gathering, data mining and exploration up to implement machine learning algorithms.
• Work closely with R&D, product team to design, deploy and evaluate ML models and optimization algorithms.
• Identify and decide on promising research and development directions, balancing short term and long-term goals.
• Communication and coordination with product and business counterparts.

Skills and Qualifications

• Sc. or Ph.D. in Computer Science/Statistics/Engineering or related field with a focus on applied statistics, AI, machine learning.
• At least 4 years of working experience in the field of data science / machine learning – MUST.
• At least 4 years programming experience in Python – MUST.
• Experience in developing deep learning models with TensorFlow, Keras, or other common frameworks – MUST.
• Experience with predictive and probabilistic models, clustering algorithms, classification models for multivariate time series data.
• Self-learner, strong can-do attitude and great interpersonal skills.
• Hands-on problem solver fit for dynamic start-up environment.

Advantages

• Experience in startup environment
• Cloud & Data center industry experience
• Networking experience

R&D | Full Time | Job ID: 1-2020

About Sensai

Sensai is on a mission to develop the best Real-Time AI powered anomaly prediction tool for data centers & Cloud solutions as an essential element in the data center automation process & SLA monitoring.

If you enjoy working in a startup then join us to develop a challenging simulated network environment which can generate effective data that helps build the next generation of intelligent, automated monitoring & troubleshooting tools.

At Sensai, we are committed to our work, customers, having fun and most meaningfully to each other’s success.

Responsibilities

• Design and develop the infrastructure for state of the art, large scale, real-time predictive AI-system based on machine learning algorithms and big data.
• Lead the design and development of automated data and machine learning pipelines.
• Responsible for the experimentation infrastructure and reducing the time and effort of transforming experiments to production-ready models.
• Interact with other teams to define interfaces and understand and resolve dependencies.
• Implement model usages from research to production, in a scalable and resilient architecture (and be part of creating and maintaining this architecture).

Skills and Qualifications

• in Computer Science/ Software Engineering, MSc. is an advantage.
• 4+ years of Software Engineer experience with Python and building production-grade products.
• 2+ years of experience in the field of machine learning and deep learning.
• Experience with machine-learning frameworks (Sklearn/Tensorflow/Keras/Pytorch etc) – advantage
• Experience with MLOPS and tools (AutoML / Vertex …) – advantage.
• Experience in development of resource-intensive, high-concurrency applications – advantage.

Advantage

• Experience in startup environment
• Cloud & Data center industry experience
• Networking experience