Machine Learning Data Engineer at BlueOptima

Bangalore, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

16 Apr, 26

Salary

0.0

Posted On

16 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Engineering, Python, SQL, GIS, Statistics, Data Analytics, Computer Vision, AWS, Docker, Kubernetes, DataOps, MLOps, Project Management, Statistical Analysis, Geospatial Analytics

Industry

Software Development

Description

Company Description RedOptima, Headquartered in London UK, RedOptima is made up of a close-knit team who are developing a first-of-its-kind road infrastructure data analytics platform, to solve one of the automotive industry’s most complex research and engineering challenges. Our market-leading collision risk analytics have the potential to influence significant aspects of the automotive industry including road infrastructure safety provisions and collision risk pricing. It harnesses Machine Learning and Big Data technologies to provide industry leading collision risk probability benchmarks and real-time risk profiling of transportation assets. We focus on truly understanding the objective and controllable antecedents to road vehicle collisions by using remotely sensed data sources. RedOptima’s technology is deployed by Road and Traffic Authorities (RTAs), Automotive OEMs, and Automotive Insurers to provide unparalleled analytics through our cloud-native platform. Location: Bangalore Department: Engineering Job Description We are seeking a ML Data Engineer with a wealth of experience creating and taking ownership of data pipelines, to consume and interpret our unique GIS dataset. The analyses you deploy will range from simple stats all the way up to machine learning solutions. Our unprecedented technology requires highly skilled and talented engineers to join a close-knit team willing to understand and take ownership of the problems they solve and the solutions they deploy. This is a great opportunity to join at the early stage of a rapidly growing company and define your own success story within it. Your team Data Engineering at RedOptima accelerates value delivery for internal and external stakeholders by providing production ready solutions & actionable insights. We cater to every aspect of RedOptima’s data, supercharging their success through data driven innovation. You will be working hands-on with a diverse team, with a variety of skill sets across the fields of Data Analytics, Machine Learning, Computer Vision, Artificial intelligence, and Geospatial analytics. The RedOptima engineering team is currently based out of our Gurgaon office. Responsibilities and tasks Applying expertise in statistics and ML to tackle real problems using our unprecedented collision risk analytics platform Identifying new opportunities to automate and create insights using our diverse data sources Staying up-to-date in cutting-edge numerical and computer vision methods in ML space Productionising models on AWS infrastructure Ownership from prototype/MVP to automation, deployment, and maintenance Deploying monitoring and DQ automation to health check solutions in production Coaching team members in solution ownership and best practice in development and design Communicating complex concepts to client-facing teams and non-experts Creating and maintaining systems that are optimised, robust and scalable Identify requirements and critical path to solve problems, give clear timeline estimates quantifying any uncertainty Take data-driven approaches to validate assumptions/issues and track progress on changes being implemented Qualifications What You Need to Succeed at RedOptima Minimum Bachelor's degree in Computer Science/Statistics/Mathematics or equivalent. 4+ years of experience with Python and SQL 4+ years of experience in data-driven analytics 3+ years using Machine learning Algorithms in the industry in e.g. Tensorflow, Keras, PyTorch 2+ years of experience managing a co-located team and project management Communicating very complex concepts to client-facing teams and non-experts Providing task time estimates and quantifying uncertainties Problem solving and analytical approaches to problems Good to have (Technical requirements/ Previous experience) 2+ years developing computer vision solutions using machine learning 2+ years handling Geographical Information Systems (GIS) data (using e.g. PostGIS, QGIS, ArcGIS, geopandas) Working knowledge and experience of Python statistics/ML tech stack (e.g. pandas, NumPy, Dask, scikit-learn, Tensorflow, Keras, PySpark, PyTorch) Statistical analysis (hypothesis testing, regression, random variables, inference) Docker, Kubernetes in production SLDC and engineering practices (Data pipelines, API workflows, CI/CD deployments) Data and ML performance monitoring (DataOps, MLOps) Additional Information Your career progression At RedOptima, we strive to strengthen your skills, widen your scope of work and develop your career fast. You will join a close-knit international team at an early stage, so expect to handle new and challenging tech implementations from day one, learning on the job through deep dives, research and direct experience. You will take sole ownership and responsibility for new data initiatives which scale as the company does. As the company continues to scale, you can also expect to mentor, onboard and lead others as one of the early-stage members of the team. Why join our team? Culture and Growth Global team with a creative, innovative and welcoming mindset Rapid career growth and opportunity to be an outstanding and visible contributor to the company's success Freedom to create your own success story in a high performance environment Training programs and Personal Development Plans for each employee Work with a unique and truly vast collection of datasets Opportunities to lead and take ownership of new software initiatives Tight-knit team with an informal and super-motivated culture Unique challenges with an immediate business impact Benefits Flexible Work from Home policy - 2 days home p/w Free drinks and snacks in the office High quality equipment (Ergonomic chairs and 32’ screens) 32 days of holidays (including bank holidays)

Responsibilities

The role involves applying expertise in statistics and machine learning to solve real problems using collision risk analytics. Responsibilities include automating insights from diverse data sources and deploying models on AWS infrastructure.