Research Scientist - Machine Learning/Artificial Intelligence

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Purpose of Job:
Responsible to lead a team of analysts to build and deploy predictive models to infuse core
business functions with deep analytical insights. The Senior Data Scientist will also work
closely with the Kinara management team to investigate strategically important business questions.
Job Responsibilities:
Lead a team through the entire analytical and machine learning model life cycle:
Define the problem statement
Build and clean datasets
Exploratory data analysis
Feature engineering
Apply ML algorithms and assess the performance
Code for deployment
Code testing and troubleshooting
Communicate Analysis to Stakeholders
Manage Data Analysts and Data Scientists
Qualifications:
Education: MS/MTech/Btech graduates or equivalent with a focus on data science and
quantitative fields (CS, Engineering, Mathematics, Economics)
Work Experience: 5+ years in a professional role with 3+ years in ML/AI
Other Requirements: ⮚ Domain knowledge in Financial Services is a big plus
Skills & Competencies
Technical Skills
⮚ Aptitude in Math and Stats
⮚ Proven experience in the use of Python, SQL, DevOps
⮚ Excellent in programming (Python), stats tools, and SQL
⮚ Working knowledge of tools and utilities - AWS, Git, Selenium, Postman,Prefect, Airflow, PySpark
Soft Skills
⮚ Deep Curiosity and Humility
⮚ Strong communications verbal and written
Role Description
This is a full-time client facing on-site role for a Data Scientist at UpSolve Solutions in Mumbai. The Data Scientist will be responsible for performing various day-to-day tasks, including data science, statistics, data analytics, data visualization, and data analysis. The role involves utilizing these skills to provide actionable insights to drive business decisions and solve complex problems.
Qualifications
- Data Science, Statistics, and Data Analytics skills
- Data Visualization and Data Analysis skills
- Strong problem-solving and critical thinking abilities
- Ability to work with large datasets and perform data preprocessing
- Proficiency in programming languages such as Python or R
- Experience with machine learning algorithms and predictive modeling
- Excellent communication and presentation skills
- Bachelor's or Master's degree in a relevant field (e.g., Computer Science, Statistics, Data Science)
- Experience in the field of video and text analytics is a plus
Key Responsibilities:
- Develop and maintain scalable Python applications for AI/ML projects.
- Design, train, and evaluate machine learning models for classification, regression, NLP, computer vision, or recommendation systems.
- Collaborate with data scientists, ML engineers, and software developers to integrate models into production systems.
- Optimize model performance and ensure low-latency inference in real-time environments.
- Work with large datasets to perform data cleaning, feature engineering, and data transformation.
- Stay current with new developments in machine learning frameworks and Python libraries.
- Write clean, testable, and efficient code following best practices.
- Develop RESTful APIs and deploy ML models via cloud or container-based solutions (e.g., AWS, Docker, Kubernetes).
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Job Purpose and Impact:
The Sr. Generative AI Engineer will architect, design and develop new and existing GenAI solutions for the organization. As a Generative AI Engineer, you will be responsible for developing and implementing products using cutting-edge generative AI and RAG to solve complex problems and drive innovation across our organization. You will work closely with data scientists, software engineers, and product managers to design, build, and deploy AI-powered solutions that enhance our products and services in Cargill. You will bring order to ambiguous scenarios and apply in depth and broad knowledge of architectural, engineering and security practices to ensure your solutions are scalable, resilient and robust and will share knowledge on modern practices and technologies to the shared engineering community.
Key Accountabilities:
• Apply software and AI engineering patterns and principles to design, develop, test, integrate, maintain and troubleshoot complex and varied Generative AI software solutions and incorporate security practices in newly developed and maintained applications.
• Collaborate with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals.
• Conduct research to stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques and identify opportunities to integrate them into our products and services, optimizing existing generative AI models and RAG for improved performance, scalability, and efficiency, developing and maintaining pipelines and RAG solutions including data preprocessing, prompt engineering, benchmarking and fine-tuning.
• Develop clear and concise documentation, including technical specifications, user guides and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.
• Participate in the engineering community by maintaining and sharing relevant technical approaches and modern skills in AI.
• Contribute to the establishment of best practices and standards for generative AI development within the organization.
• Independently handle complex issues with minimal supervision, while escalating only the most complex issues to appropriate staff.
Minimum Qualifications:
• Bachelor’s degree in a related field or equivalent experience
• Minimum of five years of related work experience
• You are proficient in Python and have experience with machine learning libraries and frameworks
• Have deep understanding of industry leading Foundation Model capabilities and its application.
• You are familiar with cloud-based Generative AI platforms and services
• Full stack software engineering experience to build products using Foundation Models
• Confirmed experience architecting applications, databases, services or integrations.
About Kloud9:
Kloud9 exists with the sole purpose of providing cloud expertise to the retail industry. Our team of cloud architects, engineers and developers help retailers launch a successful cloud initiative so you can quickly realise the benefits of cloud technology. Our standardised, proven cloud adoption methodologies reduce the cloud adoption time and effort so you can directly benefit from lower migration costs.
Kloud9 was founded with the vision of bridging the gap between E-commerce and cloud. The E-commerce of any industry is limiting and poses a huge challenge in terms of the finances spent on physical data structures.
At Kloud9, we know migrating to the cloud is the single most significant technology shift your company faces today. We are your trusted advisors in transformation and are determined to build a deep partnership along the way. Our cloud and retail experts will ease your transition to the cloud.
Our sole focus is to provide cloud expertise to retail industry giving our clients the empowerment that will take their business to the next level. Our team of proficient architects, engineers and developers have been designing, building and implementing solutions for retailers for an average of more than 20 years.
We are a cloud vendor that is both platform and technology independent. Our vendor independence not just provides us with a unique perspective into the cloud market but also ensures that we deliver the cloud solutions available that best meet our clients' requirements.
Responsibilities:
● Studying, transforming, and converting data science prototypes
● Deploying models to production
● Training and retraining models as needed
● Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their respective scores
● Analyzing the errors of the model and designing strategies to overcome them
● Identifying differences in data distribution that could affect model performance in real-world situations
● Performing statistical analysis and using results to improve models
● Supervising the data acquisition process if more data is needed
● Defining data augmentation pipelines
● Defining the pre-processing or feature engineering to be done on a given dataset
● To extend and enrich existing ML frameworks and libraries
● Understanding when the findings can be applied to business decisions
● Documenting machine learning processes
Basic requirements:
● 4+ years of IT experience in which at least 2+ years of relevant experience primarily in converting data science prototypes and deploying models to production
● Proficiency with Python and machine learning libraries such as scikit-learn, matplotlib, seaborn and pandas
● Knowledge of Big Data frameworks like Hadoop, Spark, Pig, Hive, Flume, etc
● Experience in working with ML frameworks like TensorFlow, Keras, OpenCV
● Strong written and verbal communications
● Excellent interpersonal and collaboration skills.
● Expertise in visualizing and manipulating big datasets
● Familiarity with Linux
● Ability to select hardware to run an ML model with the required latency
● Robust data modelling and data architecture skills.
● Advanced degree in Computer Science/Math/Statistics or a related discipline.
● Advanced Math and Statistics skills (linear algebra, calculus, Bayesian statistics, mean, median, variance, etc.)
Nice to have
● Familiarity with Java, and R code writing.
● Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
● Verifying data quality, and/or ensuring it via data cleaning
● Supervising the data acquisition process if more data is needed
● Finding available datasets online that could be used for training
Why Explore a Career at Kloud9:
With job opportunities in prime locations of US, London, Poland and Bengaluru, we help build your career paths in cutting edge technologies of AI, Machine Learning and Data Science. Be part of an inclusive and diverse workforce that's changing the face of retail technology with their creativity and innovative solutions. Our vested interest in our employees translates to deliver the best products and solutions to our customers.
cutting-edge technology to problems that have never been solved before, working with architecture and
product teams to collaboratively visualize, design and create machine learning models for M3LD- the
world’s first privacy platform that helps users get control of their data and enterprises to establish trustbased relationships.
KEY ACCOUNTABILITIES & ACTIVITIES
AI-ML Software
Engineer
Accountabilities
& Activities
▪ Study and transform data science prototypes
▪ Design machine learning systems
▪ Research and implement appropriate ML algorithms and tools
▪ Develop machine learning applications according to requirements
▪ Select appropriate datasets and data representation methods
▪ Run machine learning tests and experiments
▪ Perform statistical analysis and fine-tuning using test results
▪ Train and retrain systems when necessary
▪ Extend existing ML libraries and frameworks
▪ Keep abreast of developments in the field
BACKGROUND, SKILLS & QUALIFICATIONS
Knowledge,
Skills and
Experience
▪ Ability and passion to deliver extraordinary results with minimal direction
▪ Collaborating with teams to dissect complex problems and design solutions tailored to M3LD
needs
▪ Expertise in big data processing, data pipeline, machine learning, and AI processing methods.
▪ Proficiency in programming languages - e.g. Python, Java, C++, Ruby.
▪ Track-record of shipping and maintaining code in production with a commitment to high quality,
well-tested code, and automation
▪ Experience with object-oriented design, multi-threading, and synchronisation
▪ Experience with ML frameworks and libraries (Spark, tensor, OpenAI)
▪ Ability to optimize runtime with performant data structures, leveraging distributed systems and/or
cloud platforms
▪ Excellent written skills and ability to document system design documentations.
▪ Experience working in “agile” development environment and collaboration tools like Jira,
Confluence, etc.
▪ Ability to communicate effectively with cross project stakeholders both verbally and in writing
▪ Ability to collaborate with distributed teams across time zones
Qualifications ▪ 5+ years of relevant work experience in enterprise, mobile and complex solution development,
and software engineering
▪ Strong computer science fundamentals required
▪ Experience with deep learning frameworks.
▪ Strong experience in programming and statistics.
▪ Experience working with DevOps practices, Git version control, and agile development
approaches.
▪ Experience developing for major cloud platforms, including Azure, AWS, Google Cloud, and
Oracle Cloud Infrastructure is preferred.
Job Description:
- Understanding about depth and breadth of computer vision and deep learning algorithms.
- At least 2 years of experience in computer vision and or deep learning for object detection and tracking along with semantic or instance segmentation either in the academic or industrial domain.
- Experience with any machine deep learning frameworks like Tensorflow, Keras, Scikit-Learn and PyTorch.
- Experience in training models through GPU computing using NVIDIA CUDA or on the cloud.
- Ability to transform research articles into working solutions to solve real-world problems.
- Strong experience in using both basic and advanced image processing algorithms for feature engineering.
- Proficiency in Python and related packages like numpy, scikit-image, PIL, opencv, matplotlib, seaborn, etc.
- Excellent written and verbal communication skills for effectively communicating with the team and ability to present information to a varied technical and non-technical audiences.
- Must be able to produce solutions independently in an organized manner and also be able to work in a team when required.
- Must have good Object-Oriented Programing & logical analysis skills in Python.
- Experience with relational SQL & NoSQL databases including MySQL & MongoDB.
- Familiar with the basic principles of distributed computing and data modeling.
- Experience with distributed data pipeline frameworks like Celery, Apache Airflow, etc.
- Experience with NLP and NER models is a bonus.
- Experience building reusable code and libraries for future use.
- Experience building REST APIs.
Preference for candidates working in tech product companies












