Be a part of the growth story of a rapidly growing organization in AI. We are seeking a passionate Machine Learning (ML) Engineer, with a strong background in developing and deploying state-of-the-art models on Cloud. You will participate in the complete cycle of building machine learning models from conceptualization of ideas, data preparation, feature selection, training, evaluation, and productionization.
On a typical day, you might build data pipelines, develop a new machine learning algorithm, train a new model or deploy the trained model on the cloud. You will have a high degree of autonomy, ownership, and influence over your work, machine learning organizations' evolution, and the direction of the company.
- Bachelor's degree in computer science/electrical engineering or equivalent practical experience
- 7+ years of Industry experience in Data Science, ML/AI projects. Experience in productionizing machine learning in the industry setting
- Strong grasp of statistical machine learning, linear algebra, deep learning, and computer vision
- 3+ years experience with one or more general-purpose programming languages including but not limited to: R, Python.
- Experience with PyTorch or TensorFlow or other ML Frameworks.
- Experience in using Cloud services such as AWS, GCP, Azure. Understand the principles of developing cloud-native application development
In this role you will:
- Design and implement ML components, systems and tools to automate and enable our various AI industry solutions
- Apply research methodologies to identify the machine learning models to solve a business problem and deploy the model at scale.
- Own the ML pipeline from data collection, through the prototype development to production.
- Develop high-performance, scalable, and maintainable inference services that communicate with the rest of our tech stack
We are looking out for a technically driven "ML OPS Engineer" for one of our premium client
• Excellent hands-on expert knowledge of cloud platform infrastructure and administration
(Azure/AWS/GCP) with strong knowledge of cloud services integration, and cloud security
• Expertise setting up CI/CD processes, building and maintaining secure DevOps pipelines with at
least 2 major DevOps stacks (e.g., Azure DevOps, Gitlab, Argo)
• Experience with modern development methods and tooling: Containers (e.g., docker) and
container orchestration (K8s), CI/CD tools (e.g., Circle CI, Jenkins, GitHub actions, Azure
DevOps), version control (Git, GitHub, GitLab), orchestration/DAGs tools (e.g., Argo, Airflow,
• Hands-on coding skills Python 3 (e.g., API including automated testing frameworks and libraries
(e.g., pytest) and Infrastructure as Code (e.g., Terraform) and Kubernetes artifacts (e.g.,
deployments, operators, helm charts)
• Experience setting up at least one contemporary MLOps tooling (e.g., experiment tracking,
model governance, packaging, deployment, feature store)
• Practical knowledge delivering and maintaining production software such as APIs and cloud
• Knowledge of SQL (intermediate level or more preferred) and familiarity working with at least
one common RDBMS (MySQL, Postgres, SQL Server, Oracle)
Principal Accountabilities :
1. Good in communication and converting business requirements to functional requirements
2. Develop data-driven insights and machine learning models to identify and extract facts from sales, supply chain and operational data
3. Sound Knowledge and experience in statistical and data mining techniques: Regression, Random Forest, Boosting Trees, Time Series Forecasting, etc.
5. Experience in SOTA Deep Learning techniques to solve NLP problems.
6. End-to-end data collection, model development and testing, and integration into production environments.
7. Build and prototype analysis pipelines iteratively to provide insights at scale.
8. Experience in querying different data sources
9. Partner with developers and business teams for the business-oriented decisions
10. Looking for someone who dares to move on even when the path is not clear and be creative to overcome challenges in the data.
Sizzle is an exciting new startup that’s changing the world of gaming. At Sizzle, we’re building AI to automate gaming highlights, directly from Twitch and YouTube streams.
For this role, we're looking for someone that ideally loves to watch video gaming content on Twitch and YouTube. Specifically, you will help generate training data for all the AI we are building. This will include gathering screenshots, clips and other data from gaming videos on Twitch and YouTube. You will then be responsible for labeling and annotating them. You will work very closely with our AI engineers.
- Gather training data as specified by the management and engineering team
- Label and annotate all the training data
- Ensure all data is prepped and ready to feed into the AI models
- Revise the training data as specified by the engineering team
- Test the output of the AI models and update training data needs
You should have the following qualities:
- Willingness to work hard and hit deadlines
- Work well with people
- Be able to work remotely (if not in Bangalore)
- Interested in learning about AI and computer vision
- Willingness to learn rapidly on the job
- Ideally a gamer or someone interested in watching gaming content online
Data labeling, annotation, AI, computer vision, gaming
Work Experience: 0 years to 3 years
About SizzleSizzle is building AI to automate gaming highlights, directly from Twitch and YouTube videos. Presently, there are over 700 million fans around the world that watch gaming videos on Twitch and YouTube. Sizzle is creating a new highlights experience for these fans, so they can catch up on their favorite streamers and esports leagues. Sizzle is available at www.sizzle.gg .
with the engineering team to strategize and execute the development of data products
● Execute analytical experiments methodically to help solve various problems and make a true impact across
various domains and industries
NLP ENGINEER at KARZA TECHNOLOGIES
● Identify relevant data sources and sets to mine for client business needs, and collect large structured and
unstructured datasets and variables
● Devise and utilize algorithms and models to mine big data stores, perform data and error analysis to improve
models, and clean and validate data for uniformity and accuracy
● Analyze data for trends and patterns, and Interpret data with a clear objective in mind
● Implement analytical models into production by collaborating with software developers and machine
● Communicate analytic solutions to stakeholders and implement improvements as needed to operational
What you need to work with us:
● Good understanding of data structures, algorithms, and the first principles of mathematics.
● Proficient in Python and using packages like NLTK, Numpy, Pandas
● Should have worked on deep learning frameworks (like Tensorflow, Keras, PyTorch, etc)
● Hands-on experience in Natural Language Processing, Sequence, and RNN Based models
● Mathematical intuition of ML and DL algorithms
● Should be able to perform thorough model evaluation by creating hypotheses on the basis of statistical
● Should be comfortable in going through open-source code and reading research papers.
● Should be curious or thoughtful enough to answer the “WHYs” pertaining to the most cherished
observations, thumb rules, and ideas across the data science community.
Qualification and Experience Required:
● 1 - 4 years of relevant experience
● Bachelor/ Master’s degree in computer science / Computer Engineering / Information Technology
We are looking for an experienced engineer with superb technical skills. Primarily be responsible for architecting and building large scale data pipelines that delivers AI and Analytical solutions to our customers. The right candidate will enthusiastically take ownership in developing and managing a continuously improving, robust, scalable software solutions.
Although your primary responsibilities will be around back-end work, we prize individuals who are willing to step in and contribute to other areas including automation, tooling, and management applications. Experience with or desire to learn Machine Learning a plus.
- Bachelors/Masters/Phd in CS or equivalent industry experience
- Demonstrated expertise of building and shipping cloud native applications
- 5+ years of industry experience in administering (including setting up, managing, monitoring) data processing pipelines (both streaming and batch) using frameworks such as Kafka Streams, Py Spark, and streaming databases like druid or equivalent like Hive
- Strong industry expertise with containerization technologies including kubernetes (EKS/AKS), Kubeflow
- Experience with cloud platform services such as AWS, Azure or GCP especially with EKS, Managed Kafka
- 5+ Industry experience in python
- Experience with popular modern web frameworks such as Spring boot, Play framework, or Django
- Experience with scripting languages. Python experience highly desirable. Experience in API development using Swagger
- Implementing automated testing platforms and unit tests
- Proficient understanding of code versioning tools, such as Git
- Familiarity with continuous integration, Jenkins
- Architect, Design and Implement Large scale data processing pipelines using Kafka Streams, PySpark, Fluentd and Druid
- Create custom Operators for Kubernetes, Kubeflow
- Develop data ingestion processes and ETLs
- Assist in dev ops operations
- Design and Implement APIs
- Identify performance bottlenecks and bugs, and devise solutions to these problems
- Help maintain code quality, organization, and documentation
- Communicate with stakeholders regarding various aspects of solution.
- Mentor team members on best practices
Location: Ahmedabad / Pune
InFoCusp is a company working in the broad field of Computer Science, Software Engineering, and Artificial Intelligence (AI). It is headquartered in Ahmedabad, India, having a branch office in Pune.
We have worked on / are working on AI projects / algorithms-heavy projects with applications ranging in finance, healthcare, e-commerce, legal, HR/recruiting, pharmaceutical, leisure sports and computer gaming domains. All of this is based on the core concepts of data science,
computer vision, machine learning (with emphasis on deep learning), cloud computing, biomedical signal processing, text and natural language processing, distributed systems, embedded systems and the Internet of Things.
● Applying machine learning, deep learning, and signal processing on large datasets (Audio, sensors, images, videos, text) to develop models.
● Architecting large scale data analytics/modeling systems.
● Designing and programming machine learning methods and integrating them into our ML framework/pipeline.
● Analyzing data collected from various sources,
● Evaluate and validate the analysis with statistical methods. Also presenting this in a lucid form to people not familiar with the domain of data science/computer science.
● Writing specifications for algorithms, reports on data analysis, and documentation of algorithms.
● Evaluating new machine learning methods and adapting them for our
● Feature engineering to add new features that improve model
KNOWLEDGE AND SKILL REQUIREMENTS:
● Background and knowledge of recent advances in machine learning, deep learning, natural language processing, and/or image/signal/video processing with at least 3 years of professional work experience working on real-world data.
● Strong programming background, e.g. Python, C/C++, R, Java, and knowledge of software engineering concepts (OOP, design patterns).
● Knowledge of machine learning libraries Tensorflow, Jax, Keras, scikit-learn, pyTorch. Excellent mathematical skills and background, e.g. accuracy, significance tests, visualization, advanced probability concepts
● Ability to perform both independent and collaborative research.
● Excellent written and spoken communication skills.
● A proven ability to work in a cross-discipline environment in defined time frames. Knowledge and experience of deploying large-scale systems using distributed and cloud-based systems (Hadoop, Spark, Amazon EC2, Dataflow) is a big plus.
● Knowledge of systems engineering is a big plus.
● Some experience in project management and mentoring is also a big plus.
- B.E.\B. Tech\B.S. candidates' entries with significant prior experience in the aforementioned fields will be considered.
- M.E.\M.S.\M. Tech\PhD preferably in fields related to Computer Science with experience in machine learning, image and signal processing, or statistics preferred.
As an experienced Data Scientist you’ll join a team of data scientists, analysts, and software engineers
working to push the boundaries of data science in health care. We like to experiment, iterate, and
innovate with technology, from developing new algorithms specific to health care’s challenges, to
bringing the latest machine learning practices and applications developed in other industries into the
health care world. We know that algorithms are only valuable when powered by the right data, so we
focus on fully understanding the problems we need to solve, and truly understanding the data behind
them before launching into solutions – ensuring that the solutions we do land on are impactful and
• Research, conceptualize, and implement analytical approaches and predictive modeling to
evaluate scenarios, predict utilization and clinical outcomes, and recommend actions to impact
• Manage and execute on the entire model development process, including scope definition,
hypothesis formation, data cleaning and preparation, feature selection, model implementation
in production, validation and iteration, using multiple data sources.
• Provide guidance on necessary data and software infrastructure capabilities to deliver a scalable
solution across partners and support the implementation of the team’s algorithms and models
• Contribute to the development and publication in major journals, conferences showcasing
leadership in healthcare data science.
• Work closely and collaborate with Data Scientists, Machine Learning engineers, IT teams and
Business stakeholders spread out across various locations in US and India to achieve business
• Provide guidance to other Data Scientist and Machine Learning Engineers
empower healthcare payers, providers and members to quickly process medical data to
make informed decisions and reduce health care costs. You will be focusing on research,
development, strategy, operations, people management, and being a thought leader for
team members based out of India. You should have professional healthcare experience
using both structured and unstructured data to build applications. These applications
include but are not limited to machine learning, artificial intelligence, optical character
recognition, natural language processing, and integrating processes into the overall AI
pipeline to mine healthcare and medical information with high recall and other relevant
metrics. The results will be used dually for real-time operational processes with both
automated and human-based decision making as well as contribute to reducing
healthcare administrative costs. We work with all major cloud and big data vendors
offerings including (Azure, AWS, Google, IBM, etc.) to achieve our goals in healthcare and
The Director, Data Science will have the opportunity to build a team, shape team culture
and operating norms as a result of the fast-paced nature of a new, high-growth
• Strong communication and presentation skills to convey progress to a diverse group of stakeholders
• Strong expertise in data science, data engineering, software engineering, cloud vendors, big data technologies, real-time streaming applications, DevOps and product delivery
• Experience building stakeholder trust and confidence in deployed models especially via application of the algorithmic bias, interpretable machine learning,
data integrity, data quality, reproducible research and reliable engineering 24x7x365 product availability, scalability
• Expertise in healthcare privacy, federated learning, continuous integration and deployment, DevOps support
• Provide mentoring to data scientists and machine learning engineers as well as career development
• Meet project related team members for individual specific needs on a regular basis related to project/product deliverables
• Provide training and guidance for team members when required
• Provide performance feedback when required by leadership
The Experience You’ll Need (Required):
• MS/M.Tech degree or PhD in Computer Science, Mathematics, Physics or related STEM fields
• Significant healthcare data experience including but not limited to usage of claims data
• Delivered multiple data science and machine learning projects over 8+ years with values exceeding $10 Million or more and has worked on platform members exceeding 10 million lives
• 9+ years of industry experience in data science, machine learning, and artificial intelligence
• Strong expertise in data science, data engineering, software engineering, cloud vendors, big data technologies, real time streaming applications, DevOps, and product delivery
• Knows how to solve and launch real artificial intelligence and data science related problems and products along with managing and coordinating the
business process change, IT / cloud operations, meeting production level code standards
• Ownerships of key workflows part of data science life cycle like data acquisition, data quality, and results
• Experience building stakeholder trust and confidence in deployed models especially via application of algorithmic bias, interpretable machine learning,
data integrity, data quality, reproducible research, and reliable engineering 24x7x365 product availability, scalability
• Expertise in healthcare privacy, federated learning, continuous integration and deployment, DevOps support
• 3+ Years of experience managing directly five (5) or more senior level data scientists, machine learning engineers with advanced degrees and directly
made staff decisions
• Very strong understanding of mathematical concepts including but not limited to linear algebra, advanced calculus, partial differential equations, and
statistics including Bayesian approaches at master’s degree level and above
• 6+ years of programming experience in C++ or Java or Scala and data science programming languages like Python and R including strong understanding of
concepts like data structures, algorithms, compression techniques, high performance computing, distributed computing, and various computer architecture
• Very strong understanding and experience with traditional data science approaches like sampling techniques, feature engineering, classification, and
regressions, SVM, trees, model evaluations with several projects over 3+ years
• Very strong understanding and experience in Natural Language Processing,
reasoning, and understanding, information retrieval, text mining, search, with
3+ years of hands on experience
• Experience with developing and deploying several products in production with
experience in two or more of the following languages (Python, C++, Java, Scala)
• Strong Unix/Linux background and experience with at least one of the
following cloud vendors like AWS, Azure, and Google
• Three plus (3+) years hands on experience with MapR \ Cloudera \ Databricks
Big Data platform with Spark, Hive, Kafka etc.
• Three plus (3+) years of experience with high-performance computing like
Dask, CUDA distributed GPU, TPU etc.
• Presented at major conferences and/or published materials
We are looking for an engineer with ML/DL background.
Ideal candidate should have the following skillset
3) Experience building and deploying systems
4) Experience with Theano/Torch/Caffe/Keras all useful
5) Experience Data warehousing/storage/management would be a plus
6) Experience writing production software would be a plus
7) Ideal candidate should have developed their own DL architechtures apart from using open source architechtures.
8) Ideal candidate would have extensive experience with computer vision applications
Candidates would be responsible for building Deep Learning models to solve specific problems. Workflow would look as follows:
1) Define Problem Statement (input -> output)
2) Preprocess Data
3) Build DL model
4) Test on different datasets using Transfer Learning
5) Parameter Tuning
6) Deployment to production
Candidate should have experience working on Deep Learning with an engineering degree from a top tier institute (preferably IIT/BITS or equivalent)