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Graas uses predictive AI to turbo-charge growth for eCommerce businesses. We are “Growth-as-a-Service”. Graas is a technology solution provider using predictive AI to turbo-charge growth for eCommerce businesses. Graas integrates traditional data silos and applies a machine-learning AI engine, acting as an in-house data scientist to predict trends and give real-time insights and actionable recommendations for brands. The platform can also turn insights into action by seamlessly executing these recommendations across marketplace store fronts, brand.coms, social and conversational commerce, performance marketing, inventory management, warehousing, and last mile logistics - all of which impacts a brand’s bottom line, driving profitable growth.

Roles & Responsibilities:

Work on implementation of real-time and batch data pipelines for disparate data sources.

• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS technologies.
• Build and maintain an analytics layer that utilizes the underlying data to generate dashboards and provide actionable insights.
• Identify improvement areas in the current data system and implement optimizations.
• Work on specific areas of data governance including metadata management and data quality management.
• Participate in discussions with Product Management and Business stakeholders to understand functional requirements and interact with other cross-functional teams as needed to develop, test, and release features.
• Develop Proof-of-Concepts to validate new technology solutions or advancements.
• Work in an Agile Scrum team and help with planning, scoping and creation of technical solutions for the new product capabilities, through to continuous delivery to production.
• Work on building intelligent systems using various AI/ML algorithms. 

 

Desired Experience/Skill:

 

• Must have worked on Analytics Applications involving Data Lakes, Data Warehouses and Reporting Implementations.
• Experience with private and public cloud architectures with pros/cons.
• Ability to write robust code in Python and SQL for data processing. Experience in libraries such as Pandas is a must; knowledge of one of the frameworks such as Django or Flask is a plus.
• Experience in implementing data processing pipelines using AWS services: Kinesis, Lambda, Redshift/Snowflake, RDS.
• Knowledge of Kafka, Redis is preferred
• Experience on design and implementation of real-time and batch pipelines. Knowledge of Airflow is preferred.
• Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)

Machine Learning Engineer

Location: Ahmedabad / Pune
Team: Technology

Company Profile
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.

PRIMARY RESPONSIBILITIES:
● 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
purposes.
● Feature engineering to add new features that improve model
performance.

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.

EDUCATION:
- 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.

Responsibilities

• Partners with business stakeholders to translate business objectives into clearly defined analytical projects.
• Identify opportunities for text analytics and NLP to enhance the core product platform, select the best machine learning techniques for the specific business problem and then build the models that solve the problem.
• Own the end-end process, from recognizing the problem to implementing the solution.
• Define the variables and their inter-relationships and extract the data from our data repositories, leveraging infrastructure including Cloud computing solutions and relational database environments.
• Build predictive models that are accurate and robust and that help our customers to utilize the core platform to the maximum extent.

Skills and Qualification

• 12 to 15 yrs of experience.
• An advanced degree in predictive analytics, machine learning, artificial intelligence; or a degree in programming and significant experience with text analytics/NLP. He shall have a strong background in machine learning (unsupervised and supervised techniques). In particular, excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, logistic regression, MLPs, RNNs, etc.
• Experience with text mining, parsing, and classification using state-of-the-art techniques.
• Experience with information retrieval, Natural Language Processing, Natural Language
• Understanding and Neural Language Modeling.
• Ability to evaluate the quality of ML models and to define the right performance metrics for models in accordance with the requirements of the core platform.
• Experience in the Python data science ecosystem: Pandas, NumPy, SciPy, sci-kit-learn, NLTK, Gensim, etc.
• Excellent verbal and written communication skills, particularly possessing the ability to share technical results and recommendations to both technical and non-technical audiences.
• Ability to perform high-level work both independently and collaboratively as a project member or leader on multiple projects.