Data Engineer Lead

Job Description: Speech Recognition Engineer

3 years of industry experience

Responsibility:

 Development of ASR engine using frameworks like ESPNET or FairSeq or Athena or

Deep Speech using PyTorch or Tensorflow

 Assist to define technology required for Speech to Text besides core engine

and to design integration of these technologies.

 Work on improvement of model's accuracy and guide the team with best practices.

Desired experience:

 Good understanding of machine learning(ML) tools.

 Should be well versed in classical speech processing methodologies like hidden

Markov models (HMMs), Gaussian mixture models (GMMs), Artificial neural

networks (ANNs), Language modeling, etc.

 Hands-on experience of current deep learning (DL) techniques like Convolutional

neural networks (CNNs), recurrent neural networks (RNNs), long-term short-term

memory (LSTM), connectionist temporal classification (CTC), etc used for

speech processing is essential.

 The candidate should have hands-on experience and any of the end-to-end

implementation of ASR tools such as ESPNET or FairSeq or Athena or Deep

Speech

 Hands-on PyTorch and Tensorflow experience is desirable.

 Experience in techniques used for resolving issues related to accuracy, noise,

confidence scoring etc.

 Ability to implement recipes using scripting languages like bash

 Ability to develop applications using python, c++, Java

 Knowledge of Transformer Models like BERT-base. ELMo, ULM-FIT

 Experience in CI/CD pipeline, MLOps processes

 Hands-on deployment experience using cloud applications like AWS, GCP

Location: Bangalore

Desirable Skills: ML, Knowledge of Speech Recognition frameworks such as ESPNET

or FairSeq or Athena or Deep Speech etc, Hands-on experience of deep learning (DL)

techniques like CNN, RNN, LSTM etc., AWS, GCP

• Work closely with your business to identify issues and use data to propose solutions for effective decision making
• Build algorithms and design experiments to merge, manage, interrogate and extract data to supply tailored reports to colleagues, customers or the wider organisation.
• Creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc
• Querying databases and using statistical computer languages: R, Python, SLQ, etc.
• Visualizing/presenting data through various Dashboards for Data Analysis, Using Python Dash, Flask etc.
• Test data mining models to select the most appropriate ones for use on a project
• Work in a POSIX/UNIX environment to run/deploy applications
• Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
• Develop custom data models and algorithms to apply to data sets.
• Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
• Assess the effectiveness of data sources and data-gathering techniques and improve data collection methods
• Horizon scan to stay up to date with the latest technology, techniques and methods
• Coordinate with different functional teams to implement models and monitor outcomes.
• Stay curious and enthusiastic about using algorithms to solve problems and enthuse others to see the benefit of your work.

• Able to create algorithms to extract information from large data sets
• Strong knowledge of Python, R, Java or another scripting/statistical languages to automate data retrieval, manipulation and analysis.
• Experience with extracting and aggregating data from large data sets using SQL or other tools
• Strong understanding of various NLP, and NLU techniques like Named Entity Recognition, Summarization, Topic Modeling, Text Classification, Lemmatization and Stemming.
• Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, etc.
• Experience with Python libraries such as Pandas, NumPy, SciPy, Scikit-Learn
• Experience with Jupyter / Pandas / Numpy to manipulate and analyse data
• Knowledge of Machine Learning techniques and their respective pros and cons
• Strong Knowledge of various Data Science Visualization Tools like Tableau, PowerBI, D3, Plotly, etc.
• Experience using web services: Redshift, AWS, S3, Spark, DigitalOcean, etc.
• Proficiency in using query languages, such as SQL, Spark DataFrame API, etc.
• Hands-on experience in HTML, CSS, Bootstrap, JavaScript, AJAX, jQuery and Prototyping.
• Hands-on experience on C#, Javascript, .Net
• Experience in understanding and analyzing data using statistical software (e.g., Python, R, KDB+ and other relevant libraries)
• Experienced in building applications that meet enterprise needs – secure, scalable, loosely coupled design
• Strong knowledge of computer science, algorithms, and design patterns
• Strong oral and written communication, and other soft skills critical to collaborating and engage with teams

• Proficiency in shell scripting
• Proficiency in automation of tasks
• Proficiency in Pyspark/Python
• Proficiency in writing and understanding of sqoop
• Understanding of CloudEra manager
• Good understanding of RDBMS
• Good understanding of Excel

• Design AWS data ingestion frameworks and pipelines based on the specific needs driven by the Product Owners and user stories…
• Experience building Data Lake using AWS and Hands-on experience in S3, EKS, ECS, AWS Glue, AWS KMS, AWS Firehose, EMR
• Experience Apache Spark Programming with Databricks
• Experience working on NoSQL Databases such as Cassandra, HBase, and Elastic Search
• Hands on experience with leveraging CI/CD to rapidly build & test application code
• Expertise in Data governance and Data Quality
• Experience working with PCI Data and working with data scientists is a plus
• At least 4+ years of experience in the following Big Data frameworks: File Format (Parquet, AVRO, ORC), Resource Management, Distributed Processing and RDBMS
• 5+ years of experience on designing and developing Data Pipelines for Data Ingestion or Transformation using AWS technologies

• Use data to develop machine learning models that optimize decision making in Credit Risk, Fraud, Marketing, and Operations
• Implement data pipelines, new features, and algorithms that are critical to our production models
• Create scalable strategies to deploy and execute your models
• Write well designed, testable, efficient code
• Identify valuable data sources and automate collection processes.
• Undertake to preprocess of structured and unstructured data.
• Analyze large amounts of information to discover trends and patterns.

Requirements:

• 2+ years of experience in applied data science or engineering with a focus on machine learning
• Python expertise with good knowledge of machine learning libraries, tools, techniques, and frameworks (e.g. pandas, sklearn, xgboost, lightgbm, logistic regression, random forest classifier, gradient boosting regressor, etc)
• strong quantitative and programming skills with a product-driven sensibility

SpringML is looking to hire a top-notch Senior  Data Engineer who is passionate about working with data and using the latest distributed framework to process large dataset. As an Associate Data Engineer, your primary role will be to design and build data pipelines. You will be focused on helping client projects on data integration, data prep and implementing machine learning on datasets. In this role, you will work on some of the latest technologies, collaborate with partners on early win, consultative approach with clients, interact daily with executive leadership, and help build a great company. Chosen team members will be part of the core team and play a critical role in scaling up our emerging practice.

RESPONSIBILITIES:

• Ability to work as a member of a team assigned to design and implement data integration solutions.
• Build Data pipelines using standard frameworks in Hadoop, Apache Beam and other open-source solutions.
• Learn quickly – ability to understand and rapidly comprehend new areas – functional and technical – and apply detailed and critical thinking to customer solutions.
• Propose design solutions and recommend best practices for large scale data analysis

SKILLS:

• B.tech  degree in computer science, mathematics or other relevant fields.
• 4+years of experience in ETL, Data Warehouse, Visualization and building data pipelines.
• Strong Programming skills – experience and expertise in one of the following: Java, Python, Scala, C.
• Proficient in big data/distributed computing frameworks such as Apache,Spark, Kafka,
• Experience with Agile implementation methodologies

We are looking for someone with 6+ years of relevant experience working on problems in NLP or Computer Vision with a Master's degree (PhD preferred).