Research Scientist - Machine Learning/Artificial Intelligence

Hi,

PFB the Job Description for Data Science with ML

Title                                  : Data Scientist - Machine Learning

Experience                   : 5+ Yrs

Location                         : Chennai /Bengaluru

Type of hire                  : PWD and Non PWD

Employment Type    : Full Time

Notice Period            : Immediate Joiner

Working hours           : 09:00 a.m. to 06:00 p.m.

Work Days                    : Mon - Fri

About Ampera:

Ampera Technologies, a purpose driven Digital IT Services with primary focus on supporting our client with their Data, AI / ML, Accessibility and other Digital IT needs. We also ensure that equal opportunities are provided to Persons with Disabilities Talent. Ampera Technologies has its Global Headquarters in Chicago, USA and its Global Delivery Center is based out of Chennai, India. We are actively expanding our Tech Delivery team in Chennai and across India. We offer exciting benefits for our teams, such as 1) Hybrid and Remote work options available, 2) Opportunity to work directly with our Global Enterprise Clients, 3) Opportunity to learn and implement evolving Technologies, 4) Comprehensive healthcare, and 5) Conducive environment for Persons with Disability Talent meeting Physical and Digital Accessibility standards

About the Role

We are looking for a skilled Data Scientist with strong Machine Learning experience to design, develop, and deploy data-driven solutions. The role involves working with large datasets, building predictive and ML models, and collaborating with cross-functional teams to translate business problems into analytical solutions.

Key Responsibilities

• Analyze large, structured and unstructured datasets to derive actionable insights.
• Design, build, validate, and deploy Machine Learning models for prediction, classification, recommendation, and optimization.
• Apply statistical analysis, feature engineering, and model evaluation techniques.
• Work closely with business stakeholders to understand requirements and convert them into data science solutions.
• Develop end-to-end ML pipelines including data preprocessing, model training, testing, and deployment.
• Monitor model performance and retrain models as required.
• Document assumptions, methodologies, and results clearly.
• Collaborate with data engineers and software teams to integrate models into production systems.
• Stay updated with the latest advancements in data science and machine learning.

Required Skills & Qualifications

• Bachelor’s or Master’s degree in computer science, Data Science, Statistics, Mathematics, or related fields.
• 5+ years of hands-on experience in Data Science and Machine Learning.
• Strong proficiency in Python (NumPy, Pandas, Scikit-learn).
• Experience with ML algorithms:
• Regression, Classification, Clustering
• Decision Trees, Random Forest, Gradient Boosting
• SVM, KNN, Naïve Bayes
• Solid understanding of statistics, probability, and linear algebra.
• Experience with data visualization tools (Matplotlib, Seaborn, Power BI, Tableau – preferred).
• Experience working with SQL and relational databases.
• Knowledge of model evaluation metrics and optimization techniques.

Preferred / Good to Have

• Experience with Deep Learning frameworks (TensorFlow, PyTorch, Keras).
• Exposure to NLP, Computer Vision, or Time Series forecasting.
• Experience with big data technologies (Spark, Hadoop).
• Familiarity with cloud platforms (AWS, Azure, GCP).
• Experience with MLOps, CI/CD pipelines, and model deployment.

Soft Skills

• Strong analytical and problem-solving abilities.
• Excellent communication and stakeholder interaction skills.
• Ability to work independently and in cross-functional teams.
• Curiosity and willingness to learn new tools and techniques.

Accessibility & Inclusion Statement

We are committed to creating an inclusive environment for all employees, including persons with disabilities. Reasonable accommodations will be provided upon request.

Equal Opportunity Employer (EOE) Statement

Ampera Technologies is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

.

Senior Full Stack Developer – Analytics Dashboard

Job Summary

We are seeking an experienced Full Stack Developer to design and build a scalable, data-driven analytics dashboard platform. The role involves developing a modern web application that integrates with multiple external data sources, processes large datasets, and presents actionable insights through interactive dashboards.

The ideal candidate should be comfortable working across the full stack and have strong experience in building analytical or reporting systems.

Key Responsibilities

• Design and develop a full-stack web application using modern technologies.
• Build scalable backend APIs to handle data ingestion, processing, and storage.
• Develop interactive dashboards and data visualisations for business reporting.
• Implement secure user authentication and role-based access.
• Integrate with third-party APIs using OAuth and REST protocols.
• Design efficient database schemas for analytical workloads.
• Implement background jobs and scheduled tasks for data syncing.
• Ensure performance, scalability, and reliability of the system.
• Write clean, maintainable, and well-documented code.
• Collaborate with product and design teams to translate requirements into features.

Required Technical Skills

Frontend

• Strong experience with React.js
• Experience with Next.js
• Knowledge of modern UI frameworks (Tailwind, MUI, Ant Design, etc.)
• Experience building dashboards using chart libraries (Recharts, Chart.js, D3, etc.)

Backend

• Strong experience with Node.js (Express or NestJS)
• REST and/or GraphQL API development
• Background job systems (cron, queues, schedulers)
• Experience with OAuth-based integrations

Database

• Strong experience with PostgreSQL
• Data modelling and performance optimisation
• Writing complex analytical SQL queries

DevOps / Infrastructure

• Cloud platforms (AWS)
• Docker and basic containerisation
• CI/CD pipelines
• Git-based workflows

Experience & Qualifications

• 5+ years of professional full stack development experience.
• Proven experience building production-grade web applications.
• Prior experience with analytics, dashboards, or data platforms is highly preferred.
• Strong problem-solving and system design skills.
• Comfortable working in a fast-paced, product-oriented environment.

Nice to Have (Bonus Skills)

• Experience with data pipelines or ETL systems.
• Knowledge of Redis or caching systems.
• Experience with SaaS products or B2B platforms.
• Basic understanding of data science or machine learning concepts.
• Familiarity with time-series data and reporting systems.
• Familiarity with meta ads/Google ads API

Soft Skills

• Strong communication skills.
• Ability to work independently and take ownership.
• Attention to detail and focus on code quality.
• Comfortable working with ambiguous requirements.

Ideal Candidate Profile (Summary)

A senior-level full stack engineer who has built complex web applications, understands data-heavy systems, and enjoys creating analytical products with a strong focus on performance, scalability, and user experience.

Mission

Own architecture across web + backend, ship reliably, and establish patterns the team can scale on.

Responsibilities

• Lead system architecture for Next.js (web) and FastAPI (backend); own code quality, reviews, and release cadence.
• Build and maintain the web app (marketing, auth, dashboard) and a shared TS SDK (@revilo/contracts, @revilo/sdk).
• Integrate Stripe, Maps, analytics; enforce accessibility and performance baselines.
• Define CI/CD (GitHub Actions), containerization (Docker), env/promotions (staging → prod).
• Partner with Mobile and AI engineers on API/tool schemas and developer experience.

Requirements

• 6–10+ years; expert TypeScript, strong Python.
• Next.js (App Router), TanStack Query, shadcn/ui; FastAPI, Postgres, pydantic/SQLModel.
• Auth (OTP/JWT/OAuth), payments, caching, pagination, API versioning.
• Practical CI/CD and observability (logs/metrics/traces).

Nice-to-haves

• OpenAPI typegen (Zod), feature flags, background jobs/queues, Vercel/EAS.

Key Outcomes (ongoing)

• Stable architecture with typed contracts; <2% crash/error on web, p95 API latency in budget, reliable weekly releases.

About the Role

We are seeking a highly skilled and experienced AI Ops Engineer to join our team. In this role, you will be responsible for ensuring the reliability, scalability, and efficiency of our AI/ML systems in production. You will work at the intersection of software engineering, machine learning, and DevOps— helping to design, deploy, and manage AI/ML models and pipelines that power mission-critical business applications.

The ideal candidate has hands-on experience in AI/ML operations and orchestrating complex data pipelines, a strong understanding of cloud-native technologies, and a passion for building robust, automated, and scalable systems.

Key Responsibilities

• AI/ML Systems Operations: Develop and manage systems to run and monitor production AI/ML workloads, ensuring performance, availability, cost-efficiency and convenience.
• Deployment & Automation: Build and maintain ETL, ML and Agentic pipelines, ensuring reproducibility and smooth deployments across environments.
• Monitoring & Incident Response: Design observability frameworks for ML systems (alerts and notifications, latency, cost, etc.) and lead incident triage, root cause analysis, and remediation.
• Collaboration: Partner with data scientists, ML engineers, and software engineers to operationalize models at scale.
• Optimization: Continuously improve infrastructure, workflows, and automation to reduce latency, increase throughput, and minimize costs.
• Governance & Compliance: Implement MLOps best practices, including versioning, auditing, security, and compliance for data and models.
• Leadership: Mentor junior engineers and contribute to the development of AI Ops standards and playbooks.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent practical experience).
• 4+ years of experience in AI/MLOps, DevOps, SRE, Data Engineering, or with at least 2+ years in AI/ML-focused operations.
• Strong expertise with cloud platforms (AWS, Azure, GCP) and container orchestration (Kubernetes, Docker).
• Hands-on experience with ML pipelines and frameworks (MLflow, Kubeflow, Airflow, SageMaker, Vertex AI, etc.).
• Proficiency in Python and/or other scripting languages for automation.
• Familiarity with monitoring/observability tools (Prometheus, Grafana, Datadog, ELK, etc.).
• Deep understanding of CI/CD, GitOps, and Infrastructure as Code (Terraform, Helm, etc.).
• Knowledge of data governance, model drift detection, and compliance in AI systems.
• Excellent problem-solving, communication, and collaboration skills.

Nice-to-Have

• Experience in large-scale distributed systems and real-time data streaming (Kafka, Flink, Spark).
• Familiarity with data science concepts, and frameworks such as scikit-learn, Keras, PyTorch, Tensorflow, etc.
• Full Stack Development knowledge to collaborate effectively across end-to-end solution delivery
• Contributions to open-source MLOps/AI Ops tools or platforms.
• Exposure to Responsible AI practices, model fairness, and explainability frameworks

Why Join Us

• Opportunity to shape and scale AI/ML operations in a fast-growing, innovation-driven environment.
• Work alongside leading data scientists and engineers on cutting-edge AI solutions.
• Competitive compensation, benefits, and career growth opportunities.

Role : Sr Data Scientist / Tech Lead – Data Science

Number of positions : 8

Responsibilities

• Lead a team of data scientists, machine learning engineers and big data specialists
• Be the main point of contact for the customers
• Lead data mining and collection procedures
• Ensure data quality and integrity
• Interpret and analyze data problems
• Conceive, plan and prioritize data projects
• Build analytic systems and predictive models
• Test performance of data-driven products
• Visualize data and create reports
• Experiment with new models and techniques
• Align data projects with organizational goals

Requirements (please read carefully)

• Very strong in statistics fundamentals. Not all data is Big Data. The candidate should be able to derive statistical insights from very few data points if required, using traditional statistical methods.
• Msc-Statistics/ Phd.Statistics
• Education – no bar, but preferably from a Statistics academic background (eg MSc-Stats, MSc-Econometrics etc), given the first point
• Strong expertise in Python (any other statistical languages/tools like R, SAS, SPSS etc are just optional, but Python is absolutely essential). If the person is very strong in Python, but has almost nil knowledge in the other statistical tools, he/she will still be considered a good candidate for this role.
• Proven experience as a Data Scientist or similar role, for about 7-8 years
• Solid understanding of machine learning and AI concepts, especially wrt choice of apt candidate algorithms for a use case, and model evaluation.
• Good expertise in writing SQL queries (should not be dependent upon anyone else for pulling in data, joining them, data wrangling etc)
• Knowledge of data management and visualization techniques --- more from a Data Science perspective.
• Should be able to grasp business problems, ask the right questions to better understand the problem breadthwise /depthwise, design apt solutions, and explain that to the business stakeholders.
• Again, the last point above is extremely important --- should be able to identify solutions that can be explained to stakeholders, and furthermore, be able to present them in simple, direct language.

 http://www.altimetrik.com/">http://www.altimetrik.com

https://www.youtube.com/watch?v=3nUs4YxppNE&;feature=emb_rel_end">https://www.youtube.com/watch?v=3nUs4YxppNE&;feature=emb_rel_end

https://www.youtube.com/watch?v=e40r6kJdC8c">https://www.youtube.com/watch?v=e40r6kJdC8c

Job Responsibilities: 

• Identify valuable data sources and automate collection processes 
• Undertake preprocessing of structured and unstructured data. 
• Analyze large amounts of information to discover trends and patterns 
• Helping develop reports and analysis. 
• Present information using data visualization techniques. 

• Assessing tests and implementing new or upgraded software and assisting with strategic decisions on new systems. 
• Evaluating changes and updates to source production systems. 
• Develop, implement, and maintain leading-edge analytic systems, taking complicated problems and building simple frameworks 
• Providing technical expertise in data storage structures, data mining, and data cleansing. 
• Propose solutions and strategies to business challenges 

Desired Skills and Experience: 

• At least 1 year of experience in Data Analysis 
• Complete understanding of Operations Research, Data Modelling, ML, and AI concepts. 

• Knowledge of Python is mandatory, familiarity with MySQL, SQL, Scala, Java or C++ is an asset 
• Experience using visualization tools (e.g. Jupyter Notebook) and data frameworks (e.g. Hadoop) 
• Analytical mind and business acumen 
• Strong math skills (e.g. statistics, algebra) 
• Problem-solving aptitude 

• Excellent communication and presentation skills. 
• Bachelor’s / Master's Degree in Computer Science, Engineering, Data Science or other quantitative or relevant field is preferred  

• 6+ years of experience in software design, development and deployment 
• Must have extensive experience in architecture, design and development on .NET framework, C#, WPF
•  Must have experience of relational database such as My SQL and MS SQL Server
• Must have experience in Web Services, SOAP, TCP
• Must have excellent experience in debugging, Problem Solving and root cause analysis 
• Must have experience on writing Nunit test cases
•  Exposure to new tech stacks: AI, ML, BigData, Cloud, Broker Engine, Rule Engine, Report Builder
•  Strong exposure to Mean Stacks (Mongo, Express, Angular, Node and React for simple and scalable full stack applications)
• Should have good experience of creating designs & design patterns.
• Lead and Mentor the team technically