Lead Machine Learning Engineer

What you need to have:

• Leveraging your deep knowledge to provide technical leadership to take projects from zero to completion
• Architecting, building and maintaining scalable data pipelines and accessing patterns related to permissions and security
• Researching, evaluating and utilising new technologies/tools/frameworks centred around high-volume data processing
• Involving in building and deploying large scale data processing pipelines in a production environment
• Working with data scientists and other engineers to develop data pipelines for model development and productization
• Identifying gaps and implementing solutions for data security, quality and automation of processes
• Providing inputs on right tool options and model designs for use cases
• Identifying gaps and implementing solutions for data security, quality and automation of processes
• Designing scalable implementations of the models developed by our Data Scientists

Desired Candidate Profile

• 3+ years strong programming experience in PySpark and Python
• Knowledge in Python, SQL, Spark (Pyspark)
• Exposure to AWS/ Azure cloud tools and services like S3 Athena, Apache Nifi, Apache Airflow
• Analytical and problem-solving skills
• Knowledge in Scrum & code sharing Tech: Git, Jira
• Experience related to processing frameworks such as Spark, Spark Streaming, Hive, Sqoop, Kafka etc
• Deep understanding of measuring and ensuring data quality at scale and the required tooling to monitor and optimise the performance of our data pipelines
• Experience building data pipelines and data-centric applications using distributed storage platforms and shipping data production pipelines sourcing data from a diverse array of sources    

• Product Analytics: This is the first and most obvious role of the Product Analyst. At this capacity, the Product Analyst is responsible for the development and delivery of tangible consumer benefits through the product or service of the business.
• In addition, in this capacity, the Product Analyst is also responsible for measuring and monitoring the product or service’s performance as well as presenting product-related consumer, market, and competitive intelligence.
• Product Strategy: As a member of the Product team, the Product Analyst is responsible for the development and proposal of product strategies.
• Product Management Operations: The Product Analyst also has the obligation to respond in a timely manner to all requests and inquiries for product information or changes. He also performs the initial product analysis in order to assess the need for any requested changes as well as their potential impact.
• At this capacity, the Product Analyst also undertakes financial modeling on the products or services of the business as well as of the target markets in order to bring about an understanding of the relations between the product and the target market. This information is presented to the Marketing Manager and other stakeholders, when necessary.
• Additionally, the Product Analyst produces reports and makes recommendations to the Product Manager and Product Marketing Manager to be used as guidance in decision-making pertaining to the business’s new as well as existent products.
• Initiative: In this capacity, the Product Analyst ensures that there is a good flow of communication between the Product team and other teams. The Product Analyst ensures this by actively participating in team meetings and keeping everyone up to date.
• Pricing and Development: The Product Analyst has the responsibility to monitor the market, competitor activities, as well as any price movements and make recommendations that will be used in key decision making. In this function, the Product Analyst will normally liaise with other departments such as the credit/risk in the business in order to enhance and increase the efficiency of effecting price changes in accordance with market shifts.
• Customer/Market Intelligence: The Product Analyst has the obligation to drive consumer intelligence through the development of external and internal data sources that improve the business’s understanding of the product’s market, competitor activities, and consumer activities.
• In the performance of this role, the Product Analyst develops or adopts research tools, sources, and methods that further support and contribute to the business’s product.

• Excellent working knowledge on Data Warehousing /Data Migration activity using an ETL tool.
• Strong Data Integration, PostgreSQL/Oracle Database skills, Shell Scripting, Python programming, and development know-how.
• Hands-on experience in working with and generating XML documents.
• Good analytical and business process understanding capability.
• Familiarized with Data Models, Source-Target Data Mapping, Transactional, and Master Data concepts.
• Well-experienced in High level/Detailed design, Performance tuning of ETL jobs.
• Very good communication skills, interpersonal skills, stakeholder management skills, self-motivated, quick learner, team player.
• Exposure to After Sales Business Domain is highly preferred.
• Experience using HP ALM, Jira for ticketing.
• Experience release management

• Total Experience of 7-10 years and should be interested in teaching and research
• 3+ years’ experience in data engineering which includes data ingestion, preparation, provisioning, automated testing, and quality checks.
• 3+ Hands-on experience in Big Data cloud platforms like AWS and GCP, Data Lakes and Data Warehouses
• 3+ years of Big Data and Analytics Technologies. Experience in SQL, writing code in spark engine using python, scala or java Language. Experience in Spark, Scala
• Experience in designing, building, and maintaining ETL systems
• Experience in data pipeline and workflow management tools like Airflow
• Application Development background along with knowledge of Analytics libraries, opensource Natural Language Processing, statistical and big data computing libraries
• Familiarity with Visualization and Reporting Tools like Tableau, Kibana.
• Should be good at storytelling in Technology

Job Description

Want to make every line of code count? Tired of being a small cog in a big machine? Like a fast-paced environment where stuff get DONE? Wanna grow with a fast-growing company (both career and compensation)? Like to wear different hats? Join ThinkDeeply in our mission to create and apply Enterprise-Grade AI for all types of applications.

Seeking an M.L. Engineer with high aptitude toward development. Will also consider coders with high aptitude in M.L. Years of experience is important but we are also looking for interest and aptitude. As part of the early engineering team, you will have a chance to make a measurable impact in future of Thinkdeeply as well as having a significant amount of responsibility.

Experience

10+ Years

Location

Bozeman/Hyderabad

Skills

Required Skills:

Bachelors/Masters or Phd in Computer Science or related industry experience

3+ years of Industry Experience in Deep Learning Frameworks in PyTorch or TensorFlow

7+ Years of industry experience in scripting languages such as Python, R.

7+ years in software development doing at least some level of Researching / POCs, Prototyping, Productizing, Process improvement, Large-data processing / performance computing

Familiar with non-neural network methods such as Bayesian, SVM, Adaboost, Random Forests etc

Some experience in setting up large scale training data pipelines.

Some experience in using Cloud services such as AWS, GCP, Azure

Desired Skills:

Experience in building deep learning models for Computer Vision and Natural Language Processing domains

Experience in productionizing/serving machine learning in industry setting

Understand the principles of developing cloud native applications

Responsibilities

Collect, Organize and Process data pipelines for developing ML models

Research and develop novel prototypes for customers

Train, implement and evaluate shippable machine learning models

Deploy and iterate improvements of ML Models through feedback