Celigo is one of the fastest growing, Silicon Valley profitable & funded startup companies pioneering the future of cloud-based application integration with its Integrator.io iPaaS platform and pre-built Integration Apps. Over 3500 companies rely on Celigo to synchronize data, automate processes, and streamline operations by integrating their cloud applications. Our Integrator.io iPaaS platform offers a simple and powerful platform through a guided user interface, integration templates, and other tools that empower both business users and IT to easily integrate any of their cloud applications. Our core mission at Celigo is simple: to enable independent best-of-breed applications to work together as one. We believe that every independent department and every business end-user should always have choices when it comes to picking software, and that integration challenges should never stand in the way.
We are full of fresh ideas with like-minded people offering opportunities to highly-talented individuals committed to working with the highest quality products in the area of business cloud computing (SaaS).
Location - Hyderabad, India.
Celigo, as an organization, invests in research and new product innovations to bring in the best of the integration solutions and user experience to our customers. In this role, you will be responsible for looking for opportunities to broaden our scale of offering, propose innovative solutions and be instrumental in bringing them to reality.
To be successful in this role, you will need a thorough understanding of the business landscape, customer needs, and capabilities of our product offerings. You should be excited about the product, its future, and have a great thirst for technology.
WHAT YOU’LL DO
- Identify opportunities to seamlessly broaden our product offerings and design clear problem statements with well-defined business values and return-on-investments.
- Architecture design, total solution design from requirements analysis, design and engineering for the identified opportunities, applying the right ML algorithms.
- Develop state-of-the art machine learning models to solve problems in the Data Integration and Application integration space.
- Identifying Data relationships and API relationships
- NLP experience
- Time-series predictions
- Recommendation systems
- Classification systems
- Defining, designing and delivering ML architecture patterns operable in native and hybrid cloud architectures.
- Hands-on experience in implementing and deploying Machine Learning solutions (using various models, such as Linear/Logistic Regression, Support Vector Machines, (Deep) Neural Networks, Hidden Markov Models, Conditional Random Fields, Topic Modeling, Game Theory, Mechanism Design, etc.)
- Experience in design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
- Experience in effective data exploration and visualization (e.g. Excel, Power BI, Tableau, Qlik, etc.)
- Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
- Experience with open source software.
- Data Driven Self Healing systems in cloud applications
- Work experience as Enterprise Architect or Software Architect or in Technical Lead roles for large scale SaaS product(s).
- Experience with machine learning and deep learning toolkits in AWS like Sage maker, Tensor flow and other open source systems.
- Hands-on programming and architecture capabilities in Python, Java, R, or SCALA
- Hands on experience in RDBMS, NoSQL, big data stores like: Elastic, Cassandra, Hbase, Hive, HDFS
- Excellent written and oral communication skills to effectively communicate complex technical concepts in simplistic terms.
- Ability to see multiple solutions to problems and choose the right one for the situation.
- Research, analyze, recommend and select technical approaches to address challenging development and data integration problems related to ML Model training and deployment in Enterprise Applications.
- Perform research activities to identify emerging technologies and trends that may affect the Data Science/ ML life-cycle management in enterprise application portfolio.
WHAT YOU’LL NEED TO SUCCEED
- Post graduation or PhD in AI domain with strong experience in research and successful outcomes.
- 15 years of total experience in Software Product Development with at least 6 years of demonstrated technical expertise around architecting solutions around AI, ML, deep learning and related technologies for complex, large-scale SaaS product(s).
- Developing AI/ML models in real-world environments and integrating AI/ML using Cloud native or hybrid technologies into large-scale enterprise applications.
- In-depth experience in AI/ML and Data analytics services offered on Amazon Web Services cloud solution and their interdependencies. Exposure to Microsoft Azure cloud solutions is a plus.
- Specializes in at least one of the AI/ML stack (Frameworks and tools like MxNET and Tensorflow, ML platform such as Amazon SageMaker for data scientists, API-driven AI Services like Amazon Lex, Amazon Polly, Amazon Transcribe, Amazon Comprehend, and Amazon Rekognition).
- Demonstrated experience developing best practices and recommendations around tools/technologies for ML life-cycle capabilities such as Data collection, Data preparation, Feature Engineering, Model Management, MLOps, Model Deployment approaches and Model monitoring and tuning.
THE BEST CANDIDATE
- Is passionate about making a world-class software organization.
- Has experience architecting solutions around AI, ML, deep-learning for large-scale distributed platforms either as an individual contributor or as part of a team.
- Enjoys a fast-paced environment, working with a highly-talented team and shifting priorities.
- Has excellent problem solving and analytical skills.
- Is great at making data-driven decisions; should use appropriate metrics and report using them in Executive/senior leadership meetings.
- Has the ability to build strong relationships with stakeholders and key partners for the program.
- Has strong business and technical vision.
- Can stay abstract or detail oriented as the situation demands.
- Has demonstrated the ability of thinking big, bringing new ideas, building teams & infrastructure for the future.
- Learns quickly; must know when to listen, and when to take charge.