11+ QGIS Jobs in India

Job Description: 

Machine Learning / AI Engineer (with 3+ years of experience)

We are seeking a highly skilled and passionate Machine Learning / AI Engineer to join our newly established data science practice area. In this role, you will primarily focus on working with Large Language Models (LLMs) and contribute to building generative AI applications. This position offers an exciting opportunity to shape the future of AI technology while charting an interesting career path within our organization.

Responsibilities:

1. Develop and implement machine learning models: Utilize your expertise in machine learning and artificial intelligence to design, develop, and deploy cutting-edge models, with a particular emphasis on Large Language Models (LLMs). Apply your knowledge to solve complex problems and optimize performance.

2. Building generative AI applications: Collaborate with cross-functional teams to conceptualize, design, and build innovative generative AI applications. Work on projects that push the boundaries of AI technology and deliver impactful solutions to real-world problems.

3. Data preprocessing and analysis: Collect, clean, and preprocess large volumes of data for training and evaluation purposes. Conduct exploratory data analysis to gain insights and identify patterns that can enhance the performance of AI models.

4. Model training and evaluation: Develop robust training pipelines for machine learning models, incorporating best practices in model selection, feature engineering, and hyperparameter tuning. Evaluate model performance using appropriate metrics and iterate on the models to improve accuracy and efficiency.

5. Research and stay up to date: Keep abreast of the latest advancements in machine learning, natural language processing, and generative AI. Stay informed about industry trends, emerging techniques, and open-source libraries, and apply relevant findings to enhance the team's capabilities.

6. Collaborate and communicate effectively: Work closely with a multidisciplinary team of data scientists, software engineers, and domain experts to drive AI initiatives. Clearly communicate complex technical concepts and findings to both technical and non-technical stakeholders.

7. Experimentation and prototyping: Explore novel ideas, experiment with new algorithms, and prototype innovative solutions. Foster a culture of innovation and contribute to the continuous improvement of AI methodologies and practices within the organization.

Requirements:

1. Education: Bachelor's or Master's degree in Computer Science, Data Science, or a related field. Relevant certifications in machine learning, deep learning, or AI are a plus.

2. Experience: A minimum of 3+ years of professional experience as a Machine Learning / AI Engineer, with a proven track record of developing and deploying machine learning models in real-world applications.

3. Strong programming skills: Proficiency in Python and experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn, pandas). Experience with cloud platforms (e.g., AWS, Azure, GCP) for model deployment is preferred.

4. Deep-learning expertise: Strong understanding of deep learning architectures (e.g., convolutional neural networks, recurrent neural networks, transformers) and familiarity with Large Language Models (LLMs) such as GPT-3, GPT-4, or equivalent.

5. Natural Language Processing (NLP) knowledge: Familiarity with NLP techniques, including tokenization, word embeddings, named entity recognition, sentiment analysis, text classification, and language generation.

6. Data manipulation and preprocessing skills: Proficiency in data manipulation using SQL and experience with data preprocessing techniques (e.g., cleaning, normalization, feature engineering). Familiarity with big data tools (e.g., Spark) is a plus.

7. Problem-solving and analytical thinking: Strong analytical and problem-solving abilities, with a keen eye for detail. Demonstrated experience in translating complex business requirements into practical machine learning solutions.

8. Communication and collaboration: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to diverse stakeholders

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.

 PLSQL  Developer

experience of 4 to 6 years

Skills- MS SQl Server and Oracle, AWS or Azure

•            Experience in setting up RDS service in cloud technologies such as AWS or Azure

•            Strong proficiency with SQL and its variation among popular databases

•            Should be well-versed in writing stored procedures, functions, packages, using collections,

•            Skilled at optimizing large, complicated SQL statements.

•            Should have worked in migration projects.

•            Should have worked on creating reports.

•            Should be able to distinguish between normalized and de-normalized data modelling designs and use cases.

•            Knowledge of best practices when dealing with relational databases

•            Capable of troubleshooting common database issues

•            Familiar with tools that can aid with profiling server resource usage and optimizing it.

•            Proficient understanding of code versioning tools such as Git and SVN

Data Scientist

Cubera is a data company revolutionizing big data analytics and Adtech through data share value principles wherein the users entrust their data to us. We refine the art of understanding, processing, extracting, and evaluating the data that is entrusted to us. We are a gateway for brands to increase their lead efficiency as the world moves towards web3.

What you’ll do?

• Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.
• Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation, and serving.
• Research new and innovative machine learning approaches.
• Perform hands-on analysis and modeling of enormous data sets to develop insights that increase Ad Traffic and Campaign Efficacy.
• Collaborate with other data scientists, data engineers, product managers, and business stakeholders to build well-crafted, pragmatic data products.  
• Actively take on new projects and constantly try to improve the existing models and infrastructure necessary for offline and online experimentation and iteration.
• Work with your team on ambiguous problem areas in existing or new ML initiatives

What are we looking for?

• Ability to write a SQL query to pull the data you need.
• Fluency in Python and familiarity with its scientific stack such as numpy, pandas, scikit learn, matplotlib.
• Experience in Tensorflow and/or R Modelling and/or PyTorch
• Ability to understand a business problem and translate, and structure it into a data science problem. 

Job Category: Data Science

Job Type: Full Time

Job Location: Bangalore

Ganit has flipped the data science value chain as we do not start with a technique but for us, consumption comes first. With this philosophy, we have successfully scaled from being a small start-up to a 200 resource company with clients in the US, Singapore, Africa, UAE, and India. 

We are looking for experienced data enthusiasts who can make the data talk to them. 

You will: 

• Understand business problems and translate business requirements into technical requirements. 
• Conduct complex data analysis to ensure data quality & reliability i.e., make the data talk by extracting, preparing, and transforming it. 
• Identify, develop and implement statistical techniques and algorithms to address business challenges and add value to the organization. 
• Gather requirements and communicate findings in the form of a meaningful story with the stakeholders  
• Build & implement data models using predictive modelling techniques. Interact with clients and provide support for queries and delivery adoption. 
• Lead and mentor data analysts. 

We are looking for someone who has: 

• Apart from your love for data and ability to code even while sleeping you would need the following. 
• Minimum of 02 years of experience in designing and delivery of data science solutions. 
• You should have successful projects of retail/BFSI/FMCG/Manufacturing/QSR in your kitty to show-off. 
• Deep understanding of various statistical techniques, mathematical models, and algorithms to start the conversation with the data in hand. 
• Ability to choose the right model for the data and translate that into a code using R, Python, VBA, SQL, etc. 
• Bachelors/Masters degree in Engineering/Technology or MBA from Tier-1 B School or MSc. in Statistics or Mathematics 

Skillset Required:

• Regression
• Classification
• Predictive Modelling
• Prescriptive Modelling
• Python
• R
• Descriptive Modelling
• Time Series
• Clustering
•  

What is in it for you: 

• Be a part of building the biggest brand in Data science. 
• An opportunity to be a part of a young and energetic team with a strong pedigree. 
• Work on awesome projects across industries and learn from the best in the industry, while growing at a hyper rate. 

Please Note:  

At Ganit, we are looking for people who love problem solving. You are encouraged to apply even if your experience does not precisely match the job description above. Your passion and skills will stand out and set you apart—especially if your career has taken some extraordinary twists and turns over the years. We welcome diverse perspectives, people who think rigorously and are not afraid to challenge assumptions in a problem. Join us and punch above your weight! 

Ganit is an equal opportunity employer and is committed to providing a work environment that is free from harassment and discrimination. 

All recruitment, selection procedures and decisions will reflect Ganit’s commitment to providing equal opportunity. All potential candidates will be assessed according to their skills, knowledge, qualifications, and capabilities. No regard will be given to factors such as age, gender, marital status, race, religion, physical impairment, or political opinions. 

• Use data to develop machine learning models that optimize decision making in Credit Risk, Fraud, Marketing, and Operations
• Implement data pipelines, new features, and algorithms that are critical to our production models
• Create scalable strategies to deploy and execute your models
• Write well designed, testable, efficient code
• Identify valuable data sources and automate collection processes.
• Undertake to preprocess of structured and unstructured data.
• Analyze large amounts of information to discover trends and patterns.

Requirements:

• 1+ years of experience in applied data science or engineering with a focus on machine learning
• Python expertise with good knowledge of machine learning libraries, tools, techniques, and frameworks (e.g. pandas, sklearn, xgboost, lightgbm, logistic regression, random forest classifier, gradient boosting regressor etc)
• strong quantitative and programming skills with a product-driven sensibility