ML Engineer-Analyst/ Senior Analyst
Job purpose:
To design and develop machine learning and deep learning systems. Run machine learning tests andexperiments and implementing appropriate ML algorithms. Works cross-functionally with the Data Scientists, Software application developers and business groups for the development of innovative ML models. Use Agile experience to work collaboratively with other Managers/Owners in geographically distributed teams.
Accountabilities:
- Work with Data Scientists and Business Analysts to frame problems in a business context. Assist all the processes from data collection, cleaning, and preprocessing, to training models and deploying them to production.
- Understand business objectives and developing models that help to achieve them, along with metrics to track their progress.
- Explore and visualize data to gain an understanding of it, then identify differences in data distribution that could affect performance when deploying the model in the real world.
- Define validation strategies, preprocess or feature engineering to be done on a given dataset and data augmentation pipelines.
- Analyze the errors of the model and design strategies to overcome them.
- Collaborate with data engineers to build data and model pipelines, manage the infrastructure and data pipelines needed to bring code to production and demonstrate end-to-end understanding of applications (including, but not limited to, the machine learning algorithms) being created.
Qualifications & Specifications
- Bachelor's degree in Engineering /Computer Science/ Math/ Statistics or equivalent. Master's degree in relevant specification will be first preference
- Experience of machine learning algorithms and libraries
- Understanding of data structures, data modeling and software architecture.
- Deep knowledge of math, probability, statistics and algorithms
- Experience with machine learning platforms such as Microsoft Azure, Google Cloud, IBM Watson, and Amazon
- Big data environment: Hadoop, Spark
- Programming languages: Python, R, PySpark
- Supervised & Unsupervised machine learning: linear regression, logistic regression, k-means
clustering, ensemble models, random forest, svm, gradient boosting
- Sampling data: bagging & boosting, bootstrapping
- Neural networks: ANN, CNN, RNN related topics
- Deep learning: Keras, Tensorflow
- Experience with AWS Sagemaker deployment and agile methodology
About Leading Multinational Co
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Job Title -Data Scientist
Job Duties
- Data Scientist responsibilities includes planning projects and building analytics models.
- You should have a strong problem-solving ability and a knack for statistical analysis.
- If you're also able to align our data products with our business goals, we'd like to meet you. Your ultimate goal will be to help improve our products and business decisions by making the most out of our data.
Responsibilities
Own end-to-end business problems and metrics, build and implement ML solutions using cutting-edge technology.
Create scalable solutions to business problems using statistical techniques, machine learning, and NLP.
Design, experiment and evaluate highly innovative models for predictive learning
Work closely with software engineering teams to drive real-time model experiments, implementations, and new feature creations
Establish scalable, efficient, and automated processes for large-scale data analysis, model development, deployment, experimentation, and evaluation.
Research and implement novel machine learning and statistical approaches.
Requirements
2-5 years of experience in data science.
In-depth understanding of modern machine learning techniques and their mathematical underpinnings.
Demonstrated ability to build PoCs for complex, ambiguous problems and scale them up.
Strong programming skills (Python, Java)
High proficiency in at least one of the following broad areas: machine learning, statistical modelling/inference, information retrieval, data mining, NLP
Experience with SQL and NoSQL databases
Strong organizational and leadership skills
Excellent communication skills
- Own the product analytics of bidgely’s end user-facing products, measure and identify areas of improvement through data
- Liaise with Product Managers and Business Leaders to understand the product issues, priorities and hence support them through relevant product analytics
- Own the automation of product analytics through good SQL knowledge
- Develop early warning metrics for production and highlight issues and breakdowns for resolution
- Resolve client escalations and concerns regarding key business metrics
- Define and own execution
- Own the Energy Efficiency program designs, dashboard development, and monitoring of existing Energy efficiency program
- Deliver data-backed analysis and statistically proven solutions
- Research and implement best practices
- Mentor team of analysts
Qualifications and Education Requirements
- B.Tech from a premier institute with 5+ years analytics experience or Full-time MBA from a premier b-school with 3+ years of experience in analytics/business or product analytics
- Bachelor's degree in Business, Computer Science, Computer Information Systems, Engineering, Mathematics, or other business/analytical disciplines
Skills needed to excel
- Proven analytical and quantitative skills and an ability to use data and metrics to back up assumptions, develop business cases, and complete root cause
analyses - Excellent understanding of retention, churn, and acquisition of user base
- Ability to employ statistics and anomaly detection techniques for data-driven
analytics - Ability to put yourself in the shoes of the end customer and understand what
“product excellence” means - Ability to rethink existing products and use analytics to identify new features and product improvements.
- Ability to rethink existing processes and design new processes for more effective analyses
- Strong SQL knowledge, working experience with Looker and Tableau a great plus
- Strong commitment to quality visible in the thoroughness of analysis and techniques employed
- Strong project management and leadership skills
- Excellent communication (oral and written) and interpersonal skills and an ability to effectively communicate with both business and technical teams
- Ability to coach and mentor analysts on technical and analytical skills
- Good knowledge of statistics, basic machine learning, and AB Testing is
preferable - Experience as a Growth hacker and/or in Product analytics is a big plus
Job Description
We are looking for an experienced engineer to join our data science team, who will help us design, develop, and deploy machine learning models in production. You will develop robust models, prepare their deployment into production in a controlled manner, while providing appropriate means to monitor their performance and stability after deployment.
What You’ll Do will include (But not limited to):
- Preparing datasets needed to train and validate our machine learning models
- Anticipate and build solutions for problems that interrupt availability, performance, and stability in our systems, services, and products at scale.
- Defining and implementing metrics to evaluate the performance of the models, both for computing performance (such as CPU & memory usage) and for ML performance (such as precision, recall, and F1)
- Supporting the deployment of machine learning models on our infrastructure, including containerization, instrumentation, and versioning
- Supporting the whole lifecycle of our machine learning models, including gathering data for retraining, A/B testing, and redeployments
- Developing, testing, and evaluating tools for machine learning models deployment, monitoring, retraining.
- Working closely within a distributed team to analyze and apply innovative solutions over billions of documents
- Supporting solutions ranging from rule-bases, classical ML techniques to the latest deep learning systems.
- Partnering with cross-functional team members to bring large scale data engineering solutions to production
- Communicating your approach and results to a wider audience through presentations
Your Qualifications:
- Demonstrated success with machine learning in a SaaS or Cloud environment, with hands–on knowledge of model creation and deployments in production at scale
- Good knowledge of traditional machine learning methods and neural networks
- Experience with practical machine learning modeling, especially on time-series forecasting, analysis, and causal inference.
- Experience with data mining algorithms and statistical modeling techniques for anomaly detection in time series such as clustering, classification, ARIMA, and decision trees is preferred.
- Ability to implement data import, cleansing and transformation functions at scale
- Fluency in Docker, Kubernetes
- Working knowledge of relational and dimensional data models with appropriate visualization techniques such as PCA.
- Solid English skills to effectively communicate with other team members
Due to the nature of the role, it would be nice if you have also:
- Experience with large datasets and distributed computing, especially with the Google Cloud Platform
- Fluency in at least one deep learning framework: PyTorch, TensorFlow / Keras
- Experience with No–SQL and Graph databases
- Experience working in a Colab, Jupyter, or Python notebook environment
- Some experience with monitoring, analysis, and alerting tools like New Relic, Prometheus, and the ELK stack
- Knowledge of Java, Scala or Go-Lang programming languages
- Familiarity with KubeFlow
- Experience with transformers, for example the Hugging Face libraries
- Experience with OpenCV
About Egnyte
In a content critical age, Egnyte fuels business growth by enabling content-rich business processes, while also providing organizations with visibility and control over their content assets. Egnyte’s cloud-native content services platform leverages the industry’s leading content intelligence engine to deliver a simple, secure, and vendor-neutral foundation for managing enterprise content across business applications and storage repositories. More than 16,000 customers trust Egnyte to enhance employee productivity, automate data management, and reduce file-sharing cost and complexity. Investors include Google Ventures, Kleiner Perkins, Caufield & Byers, and Goldman Sachs. For more information, visit www.egnyte.com
#LI-Remote
Responsibilities:
- Designing and implementing fine-tuned production ready data/ML pipelines in Hadoop platform.
- Driving optimization, testing and tooling to improve quality.
- Reviewing and approving high level & amp; detailed design to ensure that the solution delivers to the business needs and aligns to the data & analytics architecture principles and roadmap.
- Understanding business requirements and solution design to develop and implement solutions that adhere to big data architectural guidelines and address business requirements.
- Following proper SDLC (Code review, sprint process).
- Identifying, designing, and implementing internal process improvements: automating manual processes, optimizing data delivery, etc.
- Building robust and scalable data infrastructure (both batch processing and real-time) to support needs from internal and external users.
- Understanding various data security standards and using secure data security tools to apply and adhere to the required data controls for user access in the Hadoop platform.
- Supporting and contributing to development guidelines and standards for data ingestion.
- Working with a data scientist and business analytics team to assist in data ingestion and data related technical issues.
- Designing and documenting the development & deployment flow.
Requirements:
- Experience in developing rest API services using one of the Scala frameworks.
- Ability to troubleshoot and optimize complex queries on the Spark platform
- Expert in building and optimizing ‘big data’ data/ML pipelines, architectures and data sets.
- Knowledge in modelling unstructured to structured data design.
- Experience in Big Data access and storage techniques.
- Experience in doing cost estimation based on the design and development.
- Excellent debugging skills for the technical stack mentioned above which even includes analyzing server logs and application logs.
- Highly organized, self-motivated, proactive, and ability to propose best design solutions.
- Good time management and multitasking skills to work to deadlines by working independently and as a part of a team.
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!
WE ARE GRAPHENE
Graphene is an award-winning AI company, developing customized insights and data solutions for corporate clients. With a focus on healthcare, consumer goods and financial services, our proprietary AI platform is disrupting market research with an approach that allows us to get into the mind of customers to a degree unprecedented in traditional market research.
Graphene was founded by corporate leaders from Microsoft and P&G and works closely with the Singapore Government & universities in creating cutting edge technology. We are gaining traction with many Fortune 500 companies globally.
Graphene has a 6-year track record of delivering financially sustainable growth and is one of the few start-ups which are self-funded, yet profitable and debt free.
We already have a strong bench strength of leaders in place. Now, we are looking to groom more talents for our expansion into the US. Join us and take both our growths to the next level!
WHAT WILL THE ENGINEER-ML DO?
- Primary Purpose: As part of a highly productive and creative AI (NLP) analytics team, optimize algorithms/models for performance and scalability, engineer & implement machine learning algorithms into services and pipelines to be consumed at web-scale
- Daily Grind: Interface with data scientists, project managers, and the engineering team to achieve sprint goals on the product roadmap, and ensure healthy models, endpoints, CI/CD,
- Career Progression: Senior ML Engineer, ML Architect
YOU CAN EXPECT TO
- Work in a product-development team capable of independently authoring software products.
- Guide junior programmers, set up the architecture, and follow modular development approaches.
- Design and develop code which is well documented.
- Optimize of the application for maximum speed and scalability
- Adhere to the best Information security and Devops practices.
- Research and develop new approaches to problems.
- Design and implement schemas and databases with respect to the AI application
- Cross-pollinated with other teams.
HARD AND SOFT SKILLS
Must Have
- Problem-solving abilities
- Extremely strong programming background – data structures and algorithm
- Advanced Machine Learning: TensorFlow, Keras
- Python, spaCy, NLTK, Word2Vec, Graph databases, Knowledge-graph, BERT (derived models), Hyperparameter tuning
- Experience with OOPs and design patterns
- Exposure to RDBMS/NoSQL
- Test Driven Development Methodology
Good to Have
- Working in cloud-native environments (preferably Azure)
- Microservices
- Enterprise Design Patterns
- Microservices Architecture
- Distributed Systems
- Actively engage with internal business teams to understand their challenges and deliver robust, data-driven solutions.
- Work alongside global counterparts to solve data-intensive problems using standard analytical frameworks and tools.
- Be encouraged and expected to innovate and be creative in your data analysis, problem-solving, and presentation of solutions.
- Network and collaborate with a broad range of internal business units to define and deliver joint solutions.
- Work alongside customers to leverage cutting-edge technology (machine learning, streaming analytics, and ‘real’ big data) to creatively solve problems and disrupt existing business models.
In this role, we are looking for:
- A problem-solving mindset with the ability to understand business challenges and how to apply your analytics expertise to solve them.
- The unique person who can present complex mathematical solutions in a simple manner that most will understand, including customers.
- An individual excited by innovation and new technology and eager to finds ways to employ these innovations in practice.
- A team mentality, empowered by the ability to work with a diverse set of individuals.
Basic Qualifications
- A Bachelor’s degree in Data Science, Math, Statistics, Computer Science or related field with an emphasis on analytics.
- 5+ Years professional experience in a data scientist/analyst role or similar.
- Proficiency in your statistics/analytics/visualization tool of choice, but preferably in the Microsoft Azure Suite, including Azure ML Studio and PowerBI as well as R, Python, SQL.
Preferred Qualifications
- Excellent communication, organizational transformation, and leadership skills
- Demonstrated excellence in Data Science, Business Analytics and Engineering