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Data driven decision-making is core to advertising technology at AdElement. We are looking for sharp, disciplined, and highly quantitative machine learning/ artificial intellignce engineers with big data experience and a passion for digital marketing to help drive informed decision-making. You will work with top-talent and cutting edge technology and have a unique opportunity to turn your insights into products influencing billions. The potential candidate will have an extensive background in distributed training frameworks, will have experience to deploy related machine learning models end to end, and will have some experience in data-driven decision making of machine learning infrastructure enhancement. This is your chance to leave your legacy and be part of a highly successful and growing company.
Required Skills
- 3+ years of industry experience with Java/ Python in a programming intensive role
- 3+ years of experience with one or more of the following machine learning topics: classification, clustering, optimization, recommendation system, graph mining, deep learning
- 3+ years of industry experience with distributed computing frameworks such as Hadoop/Spark, Kubernetes ecosystem, etc
- 3+ years of industry experience with popular deep learning frameworks such as Spark MLlib, Keras, Tensorflow, PyTorch, etc
- 3+ years of industry experience with major cloud computing services
- An effective communicator with the ability to explain technical concepts to a non-technical audience
- (Preferred) Prior experience with ads product development (e.g., DSP/ad-exchange/SSP)
- Able to lead a small team of AI/ML Engineers to achieve business objectives
Responsibilities
- Collaborate across multiple teams - Data Science, Operations & Engineering on unique machine learning system challenges at scale
- Leverage distributed training systems to build scalable machine learning pipelines including ETL, model training and deployments in Real-Time Bidding space.
- Design and implement solutions to optimize distributed training execution in terms of model hyperparameter optimization, model training/inference latency and system-level bottlenecks
- Research state-of-the-art machine learning infrastructures to improve data healthiness, model quality and state management during the lifecycle of ML models refresh.
- Optimize integration between popular machine learning libraries and cloud ML and data processing frameworks.
- Build Deep Learning models and algorithms with optimal parallelism and performance on CPUs/ GPUs.
- Work with top management on defining teams goals and objectives.
Education
- MTech or Ph.D. in Computer Science, Software Engineering, Mathematics or related fields
Roles & Responsibilities:
-Adopt novel and breakthrough Deep Learning/Machine Learning technology to fully solve real world problems for different industries. -Develop prototypes of machine learning models based on existing research papers.
-Utilize published/existing models to meet business requirements. Tweak existing implementations to improve efficiencies and adapt for use-case variations.
-Optimize machine learning model training and inference time. -Work closely with development and QA teams in transitioning prototypes to commercial products
-Independently work end-to-end from data collection, preparation/annotation to validation of outcomes.
-Define and develop ML infrastructure to improve efficiency of ML development workflows.
Must Have:
- Experience in productizing and deployment of ML solutions.
- AI/ML expertise areas: Computer Vision with Deep Learning. Experience with object detection, classification, recognition; document layout and understanding tasks, OCR/ICR
. - Thorough understanding of full ML pipeline, starting from data collection to model building to inference.
- Experience with Python, OpenCV and at least a few framework/libraries (TensorFlow / Keras / PyTorch / spaCy / fastText / Scikit-learn etc.)
- Years with relevant experience:
5+ -Experience or Knowledge in ML OPS.
Good to Have: NLP: Text classification, entity extraction, content summarization. AWS, Docker.
•3+ years of experience in big data & data warehousing technologies
•Experience in processing and organizing large data sets
•Experience with big data tool sets such Airflow and Oozie
•Experience working with BigQuery, Snowflake or MPP, Kafka, Azure, GCP and AWS
•Experience developing in programming languages such as SQL, Python, Java or Scala
•Experience in pulling data from variety of databases systems like SQL Server, maria DB, Cassandra
NOSQL databases
•Experience working with retail, advertising or media data at large scale
•Experience working with data science engineering, advanced data insights development
•Strong quality proponent and thrives to impress with his/her work
•Strong problem-solving skills and ability to navigate complicated database relationships
•Good written and verbal communication skills , Demonstrated ability to work with product
management and/or business users to understand their needs.
- Manages the delivery of large, complex Data Science projects using appropriate frameworks and collaborating with stake holders to manage scope and risk. Help the AI/ML Solution
- Analyst to build solution as per customer need on our platform Newgen AI Cloud. Drives profitability and continued success by managing service quality and cost and leading delivery. Proactively support sales through innovative solutions and delivery excellence.
Work location: Gurugram
Key Responsibilities:
1 Collaborate/contribute to all project phases, technical know to design, develop solutions and deploy at customer end.
2 End-to-end implementations i.e. gathering requirements, analysing, designing, coding, deployment to Production
3 Client facing role talking to client on regular basis to get requirement clarification
4. Lead the team
Core Tech Skills: Azure, Cloud Computing, Java/Scala, Python, Design Patterns and fair knowledge of Data Science. Fair Knowledge of Data Lake/DWH
Educational Qualification: Engineering graduate preferably Computer since graduate
Responsibilities:
- Should act as a technical resource for the Data Science team and be involved in creating and implementing current and future Analytics projects like data lake design, data warehouse design, etc.
- Analysis and design of ETL solutions to store/fetch data from multiple systems like Google Analytics, CleverTap, CRM systems etc.
- Developing and maintaining data pipelines for real time analytics as well as batch analytics use cases.
- Collaborate with data scientists and actively work in the feature engineering and data preparation phase of model building
- Collaborate with product development and dev ops teams in implementing the data collection and aggregation solutions
- Ensure quality and consistency of the data in Data warehouse and follow best data governance practices
- Analyse large amounts of information to discover trends and patterns
- Mine and analyse data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.\
Requirements
- Bachelor’s or Masters in a highly numerate discipline such as Engineering, Science and Economics
- 2-6 years of proven experience working as a Data Engineer preferably in ecommerce/web based or consumer technologies company
- Hands on experience of working with different big data tools like Hadoop, Spark , Flink, Kafka and so on
- Good understanding of AWS ecosystem for big data analytics
- Hands on experience in creating data pipelines either using tools or by independently writing scripts
- Hands on experience in scripting languages like Python, Scala, Unix Shell scripting and so on
- Strong problem solving skills with an emphasis on product development.
- Experience using business intelligence tools e.g. Tableau, Power BI would be an added advantage (not mandatory)
Who Are We
A research-oriented company with expertise in computer vision and artificial intelligence, at its core, Orbo is a comprehensive platform of AI-based visual enhancement stack. This way, companies can find a suitable product as per their need where deep learning powered technology can automatically improve their Imagery.
ORBO's solutions are helping BFSI, beauty and personal care digital transformation and Ecommerce image retouching industries in multiple ways.
WHY US
- Join top AI company
- Grow with your best companions
- Continuous pursuit of excellence, equality, respect
- Competitive compensation and benefits
You'll be a part of the core team and will be working directly with the founders in building and iterating upon the core products that make cameras intelligent and images more informative.
To learn more about how we work, please check out
Description:
We are looking for a computer vision engineer to lead our team in developing a factory floor analytics SaaS product. This would be a fast-paced role and the person will get an opportunity to develop an industrial grade solution from concept to deployment.
Responsibilities:
- Research and develop computer vision solutions for industries (BFSI, Beauty and personal care, E-commerce, Defence etc.)
- Lead a team of ML engineers in developing an industrial AI product from scratch
- Setup end-end Deep Learning pipeline for data ingestion, preparation, model training, validation and deployment
- Tune the models to achieve high accuracy rates and minimum latency
- Deploying developed computer vision models on edge devices after optimization to meet customer requirements
Requirements:
- Bachelor’s degree
- Understanding about depth and breadth of computer vision and deep learning algorithms.
- 4+ years of industrial experience in computer vision and/or deep learning
- Experience in taking an AI product from scratch to commercial deployment.
- Experience in Image enhancement, object detection, image segmentation, image classification algorithms
- Experience in deployment with OpenVINO, ONNXruntime and TensorRT
- Experience in deploying computer vision solutions on edge devices such as Intel Movidius and Nvidia Jetson
- Experience with any machine/deep learning frameworks like Tensorflow, and PyTorch.
- Proficient understanding of code versioning tools, such as Git
Our perfect candidate is someone that:
- is proactive and an independent problem solver
- is a constant learner. We are a fast growing start-up. We want you to grow with us!
- is a team player and good communicator
What We Offer:
- You will have fun working with a fast-paced team on a product that can impact the business model of E-commerce and BFSI industries. As the team is small, you will easily be able to see a direct impact of what you build on our customers (Trust us - it is extremely fulfilling!)
- You will be in charge of what you build and be an integral part of the product development process
- Technical and financial growth!
Roles & Responsibilities
- Proven experience with deploying and tuning Open Source components into enterprise ready production tooling Experience with datacentre (Metal as a Service – MAAS) and cloud deployment technologies (AWS or GCP Architect certificates required)
- Deep understanding of Linux from kernel mechanisms through user space management
- Experience on CI/CD (Continuous Integrations and Deployment) system solutions (Jenkins).
- Using Monitoring tools (local and on public cloud platforms) Nagios, Prometheus, Sensu, ELK, Cloud Watch, Splunk, New Relic etc. to trigger instant alerts, reports and dashboards. Work closely with the development and infrastructure teams to analyze and design solutions with four nines (99.99%) up-time, globally distributed, clustered, production and non-production virtualized infrastructure.
- Wide understanding of IP networking as well as data centre infrastructure
Skills
- Expert with software development tools and sourcecode management, understanding, managing issues, code changes and grouping them into deployment releases in a stable and measurable way to maximize production Must be expert at developing and using ansible roles and configuring deployment templates with jinja2.
- Solid understanding of data collection tools like Flume, Filebeat, Metricbeat, JMX Exporter agents.
- Extensive experience operating and tuning the kafka streaming data platform, specifically as a message queue for big data processing
- Strong understanding and must have experience:
- Apache spark framework, specifically spark core and spark streaming,
- Orchestration platforms, mesos and kubernetes,
- Data storage platforms, elasticstack, carbon, clickhouse, cassandra, ceph, hdfs
- Core presentation technologies kibana, and grafana.
- Excellent scripting and programming skills (bash, python, java, go, rust). Must have previous experience with “rust” in order to support, improve in house developed products
Certification
Red Hat Certified Architect certificate or equivalent required CCNA certificate required 3-5 years of experience running open source big data platforms