Senior Manager Machine learning

3 weeks ago

Bengaluru, India MoEngage Inc. Full time

 is an insights-led customer engagement platform, trusted by 1,+ global consumer brands. As a  Great Place to Work Company  we are a young, fast-paced and intelligent customer engagement platform that fosters a culture of innovation, ownership, freedom, and fun while building future-ready technology products. Sitting at a conflux of diverse technologies like Artificial Intelligence, Big Data, Web & Mobile platforms, MoEngage technology analyzes billions of data points generated by customers and their devices in order to predict their behavior and engage them at every touchpoint throughout their lifecycle with personalized communication.

 In just eight years since our inception, we have worked with  leading Fortune brands  such as  Deutsche Telekom, Samsung, Ally Financial, Vodafone, and McAfee  along with internet-first brands such as  Flipkart, Ola, OYO, Bigbasket, and Sharechat,  with a global presence that encompasses  35 countries.  We currently have offices in San Francisco, Boston, London, Dubai, Ho Chi Minh city, Bangkok, Kuala Lumpur, Singapore, Sydney, Vietnam, Berlin, Jakarta, and Bengaluru.

The care we give to our customers is quite high Our achievement of top service and support ratings in  Gartner's Magic Quadrant, Gartner Peer Insights, and G2 Summer Reports  is a testament to that. Another commendable quality is our people-centric culture, as we have recently been included in  Battery Ventures' top 25 private cloud computing companies . As recognized by the  DivHERsity  Awards, we are one of the top 20 diversity companies in the world, while the  Economics Times  names us as one of the Top Organizations for Women.

 Will you be able to thrive in a fast-paced environment where innovation, speed, and customer-centric thinking are the norm? Is it your passion to uncover opportunities others are unaware of and to champion them? Do you crave ownership and a chance to be a part of something that matters? If so, this may be a worthwhile opportunity for you

As part of the Engineering team at MoEngage, here are some things you can expect:

Take ownership and be responsible for what you build - no micro management Work with A players (some of the best talent in the country), and expedite your learning curve and career growth Make in India and build for the world at scale of M active users, which no other internet company in the country has seen Learn together from different teams on how they scale to millions of users and billions of messages.  Explore the latest in topics like Data Pipeline, MongoDB, ElasticSearch, Kafka, Spark, Samza and share with the team and more importantly have fun while you work on scaling MoEngage. MoEngage is looking for an experienced Machine Learning leader to join us in building the future of Machine Learning and Artificial Intelligence Products. This is a unique role comprising of 75% Data science and 25% engineering. You will be responsible for end-to-end delivery from problem discovery, ideation, solutioning with AI-first mindset and finally delivering a high-scale/low latency online-system for realising business impact. You will lead 2 teams comprising of Machine learning engineers (MLE/DS) and Software development engineers (SDE). These teams are continuously experimenting with new ML/AI techniques to enhance MoEngage’s AI capabilities. You will work closely with Engineering leadership and other teams to ensure the availability of our services, provide a stable and efficient platform, and enable other teams to strategically incorporate ML into their Products. You shall love working on bleeding tech while keeping yourself rooted firmly on the fundamentals. Technical skills: Data science and ML skills  Good hands-on experience in building complex and scalable Machine Leaning solutions. Distinctive problem-solving skills and impeccable business judgement. Apply statistics, modelling, and machine learning to improve the efficiency of systems and relevance algorithms across our business application products Conduct data analysis to make product recommendations and design A/B experiments Research, learn, design, and build scalable Machine Learning workflows Engineering skills (Basic) Good experience in software design and architecture. Knowledge of public cloud technologies and server-less & distributed architecture. Basic knowledge of micro-services, CI/CD, distributed systems, ETL Leadership skills Collaborating on product strategy with your Product Managers and non-tech counterparts to align on problem statements Ability to collaborate with product and engineering leaders to deliver solutions with strategic planning across multiple functional groups Proven ability to inspire, mentor, and develop team members to deliver value consistently Providing informal and formal performance feedback frequently, recognising achievement, and flagging opportunities for growth. Requirements BA/BS/B.Tech or MS degree with emphasis on coursework of a quantitative nature (e.g., Statistics, Computer Science, Engineering, Mathematics, Data Sciences) 8-12 years of hands-on experience with design and implementation of Machine Learning models for solving business problems 2+ years of proven management experience in leading and managing data science teams Strong experience with Python (NumPy, Scikit-learn, Pandas, pyspark) Experience with big data processing technologies such as Hadoop, Spark, or NoSQL databases Experience with data science tools such as Jupyter Notebook, R Studio, or Google Colab. Strong understanding of statistical concepts such as hypothesis testing, regression analysis, time series analysis, etc. Analytical approach and have experience in evaluating capability needs and the suitability of initiatives against the strategy Data-driven in your decision-making, willing to take calculated risks and fail fast, and aren’t afraid to raise your hand when you see areas to improve Nice to Have: Knowledge of deep learning techniques, frameworks such as PyTorch, TensorFlow, or Keras Experience with DevOps practices and tools such as Docker, Kubernetes, or Jenkins, Git. Familiarity with natural language processing techniques and libraries such as NLTK, spaCy, or transformers. Familiarity with database management systems such as MongoDB, MySQL or PostgreSQL.

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