Manager/Architect_MLOPs

Job Description:

1.Be a hands on problem solver with consultative approach, who can apply Machine Learning & Deep Learning algorithms to solve business challenges

a. Use the knowledge of wide variety of AI/ML techniques and algorithms to find what combinations of these techniques can best solve the problem

b. Improve Model accuracy to deliver greater business impact

c.Estimate business impact due to deployment of model

2.Work with the domain/customer teams to understand business context , data dictionaries and apply relevant Deep Learning solution for the given business challenge

3.Working with tools and scripts for sufficiently pre-processing the data & feature engineering for model development – Python / R / SQL / Cloud data pipelines

4.Design , develop & deploy Deep learning models using Tensorflow / Pytorch 

5.Experience in using Deep learning models with text, speech, image and video data

a.Design & Develop NLP models for Text Classification, Custom Entity Recognition, Relationship extraction, Text Summarization, Topic Modeling, Reasoning over Knowledge Graphs, Semantic Search using NLP tools like Spacy and opensource Tensorflow, Pytorch, etc

b.Design and develop Image recognition & video analysis models using Deep learning algorithms and open source tools like OpenCV

c.Knowledge of State of the art Deep learning algorithms

6.Optimize and tune Deep Learnings model for best possible accuracy

7.Use visualization tools/modules to be able to explore and analyze outcomes & for Model validation eg: using Power BI / Tableau

8.Work with application teams, in deploying models on cloud as a service or on-prem

a.Deployment of models in Test / Control framework for tracking

b.Build CI/CD pipelines for ML model deployment

9.Integrating AI&ML models with other applications using REST APIs and other connector technologies

10.Constantly upskill and update with the latest techniques and best practices. Write white papers and create demonstrable assets to summarize the AIML work and its impact.

· Technology/Subject Matter Expertise

• Sufficient expertise in machine learning, mathematical and statistical sciences
• Use of versioning & Collaborative tools like Git / Github
• Good understanding of landscape of AI solutions – cloud, GPU based compute, data security and privacy, API gateways, microservices based architecture, big data ingestion, storage and processing, CUDA Programming
• Develop prototype level ideas into a solution that can scale to industrial grade strength
• Ability to quantify & estimate the impact of ML models.

· Softskills Profile

• Curiosity to think in fresh and unique ways with the intent of breaking new ground.
• Must have the ability to share, explain and “sell” their thoughts, processes, ideas and opinions, even outside their own span of control
• Ability to think ahead, and anticipate the needs for solving the problem will be important

·        Ability to communicate key messages effectively, and articulate strong opinions in large forums

· Desirable Experience:

• Keen contributor to open source communities, and communities like Kaggle
• Ability to process Huge amount of Data using Pyspark/Hadoop
• Development & Application of Reinforcement Learning
• Knowledge of Optimization/Genetic Algorithms
• Operationalizing Deep learning model for a customer and understanding nuances of scaling such models in real scenarios
• Optimize and tune deep learning model for best possible accuracy
• Understanding of stream data processing, RPA, edge computing, AR/VR etc
• Appreciation of digital ethics, data privacy will be important
• Experience of working with AI & Cognitive services platforms like Azure ML, IBM Watson, AWS Sagemaker, Google Cloud will all be a big plus
• Experience in platforms like Data robot, Cognitive scale, H2O.AI etc will all be a big plus

We are looking for

A Natural Language Processing (NLP) expert with strong computer science fundamentals and experience in working with deep learning frameworks. You will be working at the cutting edge of NLP and Machine Learning.

Roles and Responsibilities

Work as part of a distributed team to research, build and deploy Machine Learning models for NLP.

Mentor and coach other team members

Evaluate the performance of NLP models and ideate on how they can be improved

Support internal and external NLP-facing APIs

Keep up to date on current research around NLP, Machine Learning and Deep Learning

Mandatory Requirements

Any graduation with at least 2 years of demonstrated experience as a Data Scientist.

Behavioral Skills

Strong analytical and problem-solving capabilities.

Proven ability to multi-task and deliver results within tight time frames

Must have strong verbal and written communication skills

Strong listening skills and eagerness to learn

Strong attention to detail and the ability to work efficiently in a team as well as individually

Hands-on experience with

NLP

Deep Learning

Machine Learning

Python

Bert

Requirements

Experience

• 5+ years of professional experience in implementing MLOps framework to scale up ML in production.
• Hands-on experience with Kubernetes, Kubeflow, MLflow, Sagemaker, and other ML model experiment management tools including training, inference, and evaluation.
• Experience in ML model serving (TorchServe, TensorFlow Serving, NVIDIA Triton inference server, etc.)
• Proficiency with ML model training frameworks (PyTorch, Pytorch Lightning, Tensorflow, etc.).
• Experience with GPU computing to do data and model training parallelism.
• Solid software engineering skills in developing systems for production.
• Strong expertise in Python.
• Building end-to-end data systems as an ML Engineer, Platform Engineer, or equivalent.
• Experience working with cloud data processing technologies (S3, ECR, Lambda, AWS, Spark, Dask, ElasticSearch, Presto, SQL, etc.).
• Having Geospatial / Remote sensing experience is a plus.

We are looking for an exceptionally talented Lead data engineer who has exposure in implementing AWS services to build data pipelines, api integration and designing data warehouse. Candidate with both hands-on and leadership capabilities will be ideal for this position.

Qualification: At least a bachelor’s degree in Science, Engineering, Applied Mathematics. Preferred Masters degree

Job Responsibilities:

• Total 6+ years of experience as a Data Engineer and 2+ years of experience in managing a team

• Have minimum 3 years of AWS Cloud experience.

• Well versed in languages such as Python, PySpark, SQL, NodeJS etc

• Has extensive experience in Spark ecosystem and has worked on both real time and batch processing

• Have experience in AWS Glue, EMR, DMS, Lambda, S3, DynamoDB, Step functions, Airflow, RDS, Aurora etc.

• Experience with modern Database systems such as Redshift, Presto, Hive etc.

• Worked on building data lakes in the past on S3 or Apache Hudi

• Solid understanding of Data Warehousing Concepts

• Good to have experience on tools such as Kafka or Kinesis

• Good to have AWS Developer Associate or Solutions Architect Associate Certification

• Have experience in managing a team

   3+ years of experience in deployment, monitoring, tuning, and administration of high concurrency MySQL production databases.

• Solid understanding of writing optimized SQL queries on MySQL databases
• Understanding of AWS, VPC, networking, security groups, IAM, and roles.
• Expertise in scripting in Python or Shell/Powershell
• Must have experience in large scale data migrations
• Excellent communication skills.