

Roles and Responsibilities
- Managing Availability, Performance, Capacity of infrastructure and applications.
- Building and implementing observability for applications health/performance/capacity.
- Optimizing On-call rotations and processes.
- Documenting “tribal” knowledge.
- Managing Infra-platforms like Mesos/Kubernetes,CICD,Observability (Prometheus/New Relic/ELK),Cloud Platforms (AWS/ Azure),Databases,Data Platforms Infrastructure
- Providing help in onboarding new services with production readiness review process.
- Providing reports on services SLO/Error Budgets/Alerts and Operational Overhead.
- Working with Dev and Product teams to define SLO/Error Budgets/Alerts.
- Working with Dev team to have in depth understanding of the application architecture
and its bottlenecks.
- Identifying observability gaps in product services, infrastructure and working with stake
owners to fix it.
- Managing Outages and doing detailed RCA with developers and identifying ways to
avoid that situation.
- Managing/Automating upgrades of the infrastructure services.
- Automate toil work.
Experience & Skills
- 6+ years of total experience
- Experience as an SRE/DevOps/Infrastructure Engineer on large scale microservices and infrastructure.
- A collaborative spirit with the ability to work across disciplines to influence, learn, and
deliver.
- A deep understanding of computer science, software development, and networking principles.
- Demonstrated experience with languages, such as Python, Java, Golang etc.
- Extensive experience with Linux administration and good understanding the various
linux kernel subsystems (memory, storage, network etc).
- Extensive experience in DNS, TCP/IP, UDP, GRPC, Routing and Load Balancing.
- Expertise in GitOps, Infrastructure as a Code tools such as Terraform etc.. and
- Configuration Management Tools such as Chef, Puppet, Saltstack, Ansible.
- Expertise of Amazon Web Services (AWS) and/or other relevant Cloud Infrastructure
solutions like Microsoft Azure or Google Cloud.
- Experience in building CI/CD solutions with tools such as Jenkins, GitLab, Spinnaker,
Argo etc.
- Experience in managing and deploying containerized environments using Docker,
Mesos/Kubernetes is a plus.

About Olacabs.com
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Key Profile -
Ambitious Project Manager with extensive experience in high-end Residential Interiors with demonstrated ability in planning, managing procurement, scheduling, quality control, and coordination of MEP services.
Job Profile -
- Manage Customer communication and Customer experience
- Delivery of Projects as per committed timeline & desired Quality
- To gather and share project information with Project Stakeholders
- Maintain strong relationships with Contractors, Suppliers, and Designers
- Ensure Execution at Sites as per Standard ensure execution process
- Willingness to learn new techniques for tracking projects
- Track & plan Site activities as per Master Project Schedule, identify the risk involved, and plan alternate on-site work execution strategies accordingly
- Verify the bills submitted by Contractors, suppliers post checking on-site measurements of work carried out at the site
- Coach & train Project Executives to ensure all Standard practices are getting followed as far as on-site execution and reporting are concerned.
Requirements
Desired Candidate Skills -
- Strong Communication Skills
- Technical Knowledge of High end Residential Interior Work
- Should be able to manage team of 3-4 people
- Knowledge of current market rates (Material & Labour rates) for various Residential Interior works

What you will do:
- Creating and updating proprietary models/spreadsheets for the prospective investments
- Analysing financial information and conducting analytic and strategic research.
- Inputting data into proprietary financial models and ensuring the accuracy of data and output based on the data.
- Creating Automations using VBA and other tools wherever needed.
- Compiling historical data in respect of stocks and companies from publicly available sources.
- Updating and maintaining databases to track relevant financial, economic or other indicators which may be relevant to the sector and/or region under coverage
- Assisting with other company and industry related analysis as may be required by the Fund Manager
- Monitoring relevant market news and information
- Assisting with the preparation and development of research reports, industry primers and marketing presentations.
- Financial Modelling Experience is a must and a person should be excellent at this. This is the main part of the job along with research on the Financial Numbers
- Excellent understanding of Financial Statements and Accounting Standards.
- Qualified CA
- Financial Statements Audit experience preferred
- The ability to work independently and proactively
- Person should be passionate for Equities
- Strong proficiency in Advanced Excel, VBA.
- Proficiency in data science tools and languages (SQL and Python) will be considered as a great positive but not a necessary requirement
- Ensuring efficient, accurate and timely processing of employees’ payroll.
- Being responsible for accounting reconciliation and analysis regarding payroll.
- Compiling summaries of earnings, deductions, leaves, taxes etc. and reporting the same to the management.
- Maintaining payroll operations by following relevant policies and procedures.
- Collecting, calculating, updating and maintaining payroll-related data and reporting the same to the management in regular intervals.
- Ensuring that the payroll-related documents are correct and accurate.
- Ensuring compliance of rules, laws & regulations while processing payroll and also while managing all the payroll related activities.
- Answering employee queries regarding payroll and also handling escalations or issues, if any.
- Handling and resolving discrepancies related to payroll, if any.
- Participating in payroll audits.
What you need to have:
- Must be either a Finance graduate / ICWA / MBA Finance / CA Inter.
- 5-7 years of relevant work experience in payroll function.
- Handled in and out payroll inputs, variance analysis and also understands drivers to payroll cost.
- Excellent communication skills and also with an excellent analytical mind.

We are looking for an outstanding ML Architect (Deployments) with expertise in deploying Machine Learning solutions/models into production and scaling them to serve millions of customers. A candidate with an adaptable and productive working style which fits in a fast-moving environment.
Skills:
- 5+ years deploying Machine Learning pipelines in large enterprise production systems.
- Experience developing end to end ML solutions from business hypothesis to deployment / understanding the entirety of the ML development life cycle.
- Expert in modern software development practices; solid experience using source control management (CI/CD).
- Proficient in designing relevant architecture / microservices to fulfil application integration, model monitoring, training / re-training, model management, model deployment, model experimentation/development, alert mechanisms.
- Experience with public cloud platforms (Azure, AWS, GCP).
- Serverless services like lambda, azure functions, and/or cloud functions.
- Orchestration services like data factory, data pipeline, and/or data flow.
- Data science workbench/managed services like azure machine learning, sagemaker, and/or AI platform.
- Data warehouse services like snowflake, redshift, bigquery, azure sql dw, AWS Redshift.
- Distributed computing services like Pyspark, EMR, Databricks.
- Data storage services like cloud storage, S3, blob, S3 Glacier.
- Data visualization tools like Power BI, Tableau, Quicksight, and/or Qlik.
- Proven experience serving up predictive algorithms and analytics through batch and real-time APIs.
- Solid working experience with software engineers, data scientists, product owners, business analysts, project managers, and business stakeholders to design the holistic solution.
- Strong technical acumen around automated testing.
- Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
- Strong hands-on experience with statistical packages and ML libraries (e.g., Python scikit learn, Spark MLlib, etc.)
- Experience in effective data exploration and visualization (e.g., Excel, Power BI, Tableau, Qlik, etc.)
- Experience in developing and debugging in one or more of the languages Java, Python.
- Ability to work in cross functional teams.
- Apply Machine Learning techniques in production including, but not limited to, neuralnets, regression, decision trees, random forests, ensembles, SVM, Bayesian models, K-Means, etc.
Roles and Responsibilities:
Deploying ML models into production, and scaling them to serve millions of customers.
Technical solutioning skills with deep understanding of technical API integrations, AI / Data Science, BigData and public cloud architectures / deployments in a SaaS environment.
Strong stakeholder relationship management skills - able to influence and manage the expectations of senior executives.
Strong networking skills with the ability to build and maintain strong relationships with both business, operations and technology teams internally and externally.
Provide software design and programming support to projects.
Qualifications & Experience:
Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Machine Learning Architect (Deployments) or a similar role for 5-7 years.
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5. Immediate Joiner
6. are available for 6 months internship


Kindly Note: This job is NOT 'Work from home'.

Experience in Java (2+ years)
- Experience in SprintBoot(2+years)
- Good Knowledge of Microservice Concept
- Framework: Springboot, Spring Security, JAX-RS, Hystrix, Kafka
- ORM: Spring Data JPA. Hibernate
- Cloud Service: AWS(MSK, S3), Serverless lambda Functions
- Build tools: Maven, Gradle

