Applied Machine Learning Engineer

The role involves computer vision tasks including development, customization and training of Convolutional Neural Networks (CNNs); application of ML techniques (SVM, regression, clustering etc. ) and traditional Image Processing (OpenCV etc. ). The role is research focused and would involve going through and implementing existing research papers, deep dive of problem analysis, generating new ideas, automating and optimizing key processes.

 

Requirements:

• 2 - 4 years of relevant experience in solving complex real-world problems at scale via deep learning, computer vision or AI
• Python, cuDNN, Tensorflow/PyTorch/Keras (or similar Deep Learning frameworks).
• CNNs, RNNs, Transfer learning (for image classification, segmentation, object detection etc).
• Image Processing techniques using OpenCV or other white-box image feature extraction algorithms.
• End to end deployment of deep learning models.

Please note - This is a 100% remote opportunity and you can work from any location.

 

About the team:

You will be a part of Cactus Labs which is the R&D Cell of Cactus Communications. Cactus Labs is a high impact cell that works to solve complex technical and business problems that help keep us strategically competitive in the industry. We are a multi-cultural team spread across multiple countries. We work in the domain of AI/ML especially with Text (NLP - Natural Language Processing), Language Understanding, Explainable AI, Big Data, AR/VR etc.

 

The opportunity: Within Cactus Labs you will work with the Big Data team. This team manages Terabytes of data coming from different sources. We are re-orchestrating data pipelines to handle this data at scale and improve visibility and robustness. We operate across all the three Cloud Platforms and leverage the best of them.

 

In this role, you will get to own a component end to end. You will also get to work on cloud platform and learn to design distributed data processing systems to operate at scale.

 

Responsibilities:

• Collaborate with a team of Big Data Engineers, Big Data and Cloud Architects and Domain SMEs to drive the product ahead
• Stay up to date with the progress of in the domain since We work on cutting-edge technologies and are constantly trying new things out
• Build solutions for massive scale. This requires extensive benchmarking to pick the right approach
• Understand the data in and out, and make sense of it. You will at times need to draw conclusions and present it to the business users
• Be independent, self-driven and highly motivated. While you will have the best people to learn from and access to various courses or training materials, we expect you to take charge of your growth and learning.

 

Expectations from you:

• 1-3 Year of relevant experience in Big Data with pySpark
• Hands on experience of distributed computing and Big Data Ecosystem - Hadoop, HDFS, Spark etc
• Good understanding of data lake and their importance in a Big Data Ecosystem
• Experience of working in the Cloud Environment (AWS, Azure or GCP)
• You like to work without a lot of supervision or micromanagement.
• Above all, you get excited by data. You like to dive deep, mine patterns and draw conclusions. You believe in making data driven decisions and helping the team look for the pattern as well.

 

Preferred skills:

• Familiarity with search engines like Elasticsearch and Bigdata warehouses systems like AWS Athena, Google Big Query etc
• Building data pipelines using Airflow
• Experience of working in AWS Cloud Environment
• Knowledge of NLP and ML

Glance – An InMobi Group Company:

Glance is an AI-first Screen Zero content discovery platform, and it’s scaled massively in the last few months to one of the largest platforms in India. Glance is a lock-screen first mobile content platform set up within InMobi. The average mobile phone user unlocks their phone >150 times a day. Glance aims to be there, providing visually rich, easy to consume content to entertain and inform mobile users - one unlock at a time. Glance is live on more than 80 millions of mobile phones in India already, and we are only getting started on this journey! We are now into phase 2 of the Glance story - we are going global!

Roposo is part of the Glance family. It is a short video entertainment platform. All the videos created here are user generated (via upload or Roposo creation tools in camera) and there are many communities creating these videos on various themes we call channels. Around 4 million videos are created every month on Roposo and power Roposo channels, some of the channels are - HaHa TV (for comedy videos), News, Beats (for singing/ dance performances) along with a For You (personalized for a user) and Your Feed (for videos of people a user follows).

 

What’s the Glance family like?

Consistently featured among the “Great Places to Work” in India since 2017, our culture is our true north, enabling us to think big, solve complex challenges and grow with new opportunities. Glanciers are passionate and driven, creative and fun-loving, take ownership and are results-focused. We invite you to free yourself, dream big and chase your passion.

 

What can we promise? 

We offer an opportunity to have an immediate impact on the company and our products. The work that you shall do will be mission critical for Glance and will be critical for optimizing tech operations, working with highly capable and ambitious peer groups. At Glance, you get food for your body, soul, and mind with daily meals, gym, and yoga classes, cutting-edge training and tools, cocktails at drink cart Thursdays and fun at work on Funky Fridays. We even promise to let you bring your kids and pets to work. 

 

What you will be doing?

Glance is looking for a Data Scientist who will design and develop processes and systems to analyze high volume, diverse "big data" sources using advanced mathematical, statistical, querying, and reporting methods. Will use machine learning techniques and statistical analysis to predict outcomes and behaviors. Interacts with business partners to identify questions for data analysis and experiments. Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and or prepares output from analysis and experiments to business partners. 

You will be working with Product leadership, taking high-level objectives and developing solutions that fulfil these requirements. Stakeholder management across Eng, Product and Business teams will be required.

 

Basic Qualifications:

• Five+ years experience working in a Data Science role
• Extensive experience developing and deploying ML models in real world environments
• Bachelor's degree in Computer Science, Mathematics, Statistics, or other analytical fields
• Exceptional familiarity with Python, Java, Spark or other open-source software with data science libraries
• Experience in advanced math and statistics
• Excellent familiarity with command line linux environment
• Able to understand various data structures and common methods in data transformation
• Experience deploying machine learning models and measuring their impact
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.

 

Preferred Qualifications

• Experience developing recommendation systems
• Experience developing and deploying deep learning models
• Bachelor’s or Master's Degree or PhD that included coursework in statistics, machine learning or data analysis
• Five+ years experience working with Hadoop, a NoSQL Database or other big data infrastructure
• Experience with being actively engaged in data science or other research-oriented position
• You would be comfortable collaborating with cross-functional teams.
• Active personal GitHub account.

Couture.ai is building a patent-pending AI platform targeted towards vertical-specific solutions. The platform is already licensed by Reliance Jio and few European retailers, to empower real-time experiences for their combined >200 million end users. For this role, credible display of innovation in past projects (or academia) is a must. We are looking for a candidate who lives and talks Data & Algorithms, love to play with BigData engineering, hands-on with Apache Spark, Kafka, RDBMS/NoSQL DBs, Big Data Analytics and handling Unix & Production Server. Tier-1 college (BE from IITs, BITS-Pilani, top NITs, IIITs or MS in Stanford, Berkley, CMU, UW–Madison) or exceptionally bright work history is a must. Let us know if this interests you to explore the profile further.

Responsibilities:

• Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world.
• Verifying data quality, and/or ensuring it via data cleaning.
• Able to adapt and work fast in producing the output which upgrades the decision making of stakeholders using ML.
• To design and develop Machine Learning systems and schemes. 
• To perform statistical analysis and fine-tune models using test results.
• To train and retrain ML systems and models as and when necessary. 
• To deploy ML models in production and maintain the cost of cloud infrastructure.
• To develop Machine Learning apps according to client and data scientist requirements.
• To analyze the problem-solving capabilities and use-cases of ML algorithms and rank them by how successful they are in meeting the objective.

Technical Knowledge:

• Worked with real time problems, solved them using ML and deep learning models deployed in real time and should have some awesome projects under his belt to showcase. 
• Proficiency in Python and experience with working with Jupyter Framework, Google collab and cloud hosted notebooks such as AWS sagemaker, DataBricks etc.
• Proficiency in working with libraries Sklearn, Tensorflow, Open CV2, Pyspark,  Pandas, Numpy and related libraries.
• Expert in visualising and manipulating complex datasets.
• Proficiency in working with visualisation libraries such as seaborn, plotly, matplotlib etc.
• Proficiency in Linear Algebra, statistics and probability required for Machine Learning.
• Proficiency in ML Based algorithms for example, Gradient boosting, stacked Machine learning, classification algorithms and deep learning algorithms. Need to have experience in hypertuning various models and comparing the results of algorithm performance.
• Big data Technologies such as Hadoop stack and Spark. 
• Basic use of clouds (VM’s example EC2).
• Brownie points for Kubernetes and Task Queues.      
• Strong written and verbal communications.
• Experience working in an Agile environment.

We’re looking to hire someone to help scale Machine Learning and NLP efforts at Episource. You’ll work with the team that develops the models powering Episource’s product focused on NLP driven medical coding. Some of the problems include improving our ICD code recommendations , clinical named entity recognition and information extraction from clinical notes.

This is a role for highly technical machine learning & data engineers who combine outstanding oral and written communication skills, and the ability to code up prototypes and productionalize using a large range of tools, algorithms, and languages. Most importantly they need to have the ability to autonomously plan and organize their work assignments based on high-level team goals.

You will be responsible for setting an agenda to develop and ship machine learning models that positively impact the business, working with partners across the company including operations and engineering. You will use research results to shape strategy for the company, and help build a foundation of tools and practices used by quantitative staff across the company.

What you will achieve:

• Define the research vision for data science, and oversee planning, staffing, and prioritization to make sure the team is advancing that roadmap

• Invest in your team’s skills, tools, and processes to improve their velocity, including working with engineering counterparts to shape the roadmap for machine learning needs

• Hire, retain, and develop talented and diverse staff through ownership of our data science hiring processes, brand, and functional leadership of data scientists

• Evangelise machine learning and AI internally and externally, including attending conferences and being a thought leader in the space

• Partner with the executive team and other business leaders to deliver cross-functional research work and models

Required Skills:

• Strong background in classical machine learning and machine learning deployments is a must and preferably with 4-8 years of experience

• Knowledge of deep learning & NLP

• Hands-on experience in TensorFlow/PyTorch, Scikit-Learn, Python, Apache Spark & Big Data platforms to manipulate large-scale structured and unstructured datasets.

• Experience with GPU computing is a plus.

• Professional experience as a data science leader, setting the vision for how to most effectively use data in your organization. This could be through technical leadership with ownership over a research agenda, or developing a team as a personnel manager in a new area at a larger company.

• Expert-level experience with a wide range of quantitative methods that can be applied to business problems.

• Evidence you’ve successfully been able to scope, deliver and sell your own research in a way that shifts the agenda of a large organization.

• Excellent written and verbal communication skills on quantitative topics for a variety of audiences: product managers, designers, engineers, and business leaders.

• Fluent in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and modeling

Qualifications

• Professional experience as a data science leader, setting the vision for how to most effectively use data in your organization

• Expert-level experience with machine learning that can be applied to business problems

• Evidence you’ve successfully been able to scope, deliver and sell your own work in a way that shifts the agenda of a large organization

• Fluent in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and modeling

• Degree in a field that has very applicable use of data science / statistics techniques (e.g. statistics, applied math, computer science, OR a science field with direct statistics application)

• 5+ years of industry experience in data science and machine learning, preferably at a software product company

• 3+ years of experience managing data science teams, incl. managing/grooming managers beneath you

• 3+ years of experience partnering with executive staff on data topics

• Experience with Big Data, Neural network (deep learning), and reinforcement learning • Ability to design machine learning systems • Research and implement appropriate ML algorithms and tools • Develop machine learning applications according to requirements • Select appropriate datasets and data representation methods • Run machine learning tests and experiments • Perform statistical analysis and fine-tuning using test results • Extend existing ML libraries and frameworks • Keep abreast of developments in the field • Understanding of data structures, data modeling and software architecture • Deep knowledge of math, probability, statistics and algorithms • Ability to write robust code in Python, Java and R Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)

Required Skill Set: -5+ years of hands-on experience in delivering results-driven analytics solutions with proven business value - Great consulting and quantitative skills, detail-oriented approach, with proven expertise in developing solutions using SQL, R, Python or such tools - A background in Statistics / Econometrics / Applied Math / Operations Research would be considered a plus -Exposure to working with globally dispersed teams based out of India or other offshore locations Role Description/ Responsibilities: Be the face of LatentView in the client's organization and help define analytics-driven consulting solutions to business problems -Translate business problems into analytic solution requirements and work with the LatentView team to develop high-quality solutions "- Communicate effectively with client / offshore team to manage client expectations and ensure timeliness and quality of insights -Develop expertise in clients business and help translate that into increasingly high value-added advisory solutions to client -Oversee Project Delivery to ensure the team meets the quality, productivity and SLA objectives - Grow the Account in terms of revenue and the size of the team You should Apply if you want to: - Change the world with Math and Models: At the core, we believe that analytics can help drive business transformation and lasting competitive advantage. We work with a heavy mix of algorithms, analysis, large databases and ROI to positively transform many a client- business performance - Make a direct impact on business: Your contribution to delivering results-driven solutions can potentially lead to millions of dollars of additional revenue or profit for our clients - Thrive in a Fast-pace Environment: You work in small teams, in an entrepreneurial environment, and a meritorious culture that values speed, growth, diversity and contribution - Work with great people: Our selection process ensures that we hire only the very best, while more than 50% of our analysts and 90% of our managers are alumni/alumna of prestigious global institutions

About the job: - You will architect, code and deploy ML models (from scratch) to predict credit risk. - You will design, run, and analyze A/B and multivariate tests to test hypotheses aimed at optimizing user experience and portfolio risk. - You will perform data exploration and build statistical models on user behavior to discover opportunities for decreasing user defaults. And you must truly be excited about this part. - You’ll use behavioral and social data to gain insights into how humans make financial choices - You will spend a lot of time in building out predictive features from super sparse data sources. - You’ll continually acquire new data sources to develop a rich dataset that characterizes risk. - You will code, drink, breathe and live python, sklearn and pandas. It’s good to have experience in these but not a necessity - as long as you’re super comfortable in a language of your choice. About you: - You’ve strong computer science fundamentals - You’ve strong understanding of ML algorithms - Ideally, you have 2+ years of experience in using ML in industry environment - You know how to run tests and understand their results from a statistical perspective - You love freedom and hate being micromanaged. You own products end to end - You have a strong desire to learn and use the latest machine learning algorithms - It will be great if you have one of the following to share - a kaggle or a github profile - Degree in statistics/quant/engineering from Tier-1 institutes.