Data scientists

About UpSolve

Work on cutting-edge tech stack. Build innovative solutions. Computer Vision, NLP, Video Analytics and IOT.

Job Role

• Ideate use cases to include recent tech releases.
• Discuss business plans and assist teams in aligning with dynamic KPIs.
• Design solution architecture from input to infrastructure and services used to data store.

Job Requirements

• Working knowledge about Azure Cognitive Services.
• Project Experience in building AI solutions like Chatbots, sentiment analysis, Image Classification, etc.
• Quick Learner and Problem Solver.

Job Qualifications

• Work Experience: 2 years +
• Education: Computer Science/IT Engineer
• Location: Mumbai

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.

Key Roles/Responsibilities: –

• Develop an understanding of business obstacles, create

• solutions based on advanced analytics and draw implications for

• model development

• Combine, explore and draw insights from data. Often large and

• complex data assets from different parts of the business.

• Design and build explorative, predictive- or prescriptive

• models, utilizing optimization, simulation and machine learning

• techniques

• Prototype and pilot new solutions and be a part of the aim

• of ‘productifying’ those valuable solutions that can have impact at a

• global scale

• Guides and coaches other chapter colleagues to help solve

• data/technical problems at an operational level, and in

• methodologies to help improve development processes

• Identifies and interprets trends and patterns in complex data sets to

• enable the business to take data-driven decisions

• Develop, train, and optimize machine learning models using Python, ML algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and other relevant technologies.
• Implement MLOps best practices, including model deployment, monitoring, and versioning.
• Utilize Vertex AI, MLFlow, KubeFlow, TFX, and other relevant MLOps tools and frameworks to streamline the machine learning lifecycle.
• Collaborate with cross-functional teams to design and implement CI/CD pipelines for continuous integration and deployment using tools such as GitHub Actions, TeamCity, and similar platforms.
• Conduct research and stay up-to-date with the latest advancements in machine learning, deep learning, and MLOps technologies.
• Provide guidance and support to data scientists and software engineers on best practices for machine learning development and deployment.
• Assist in developing tooling strategies by evaluating various options, vendors, and product roadmaps to enhance the efficiency and effectiveness of our AI and data science initiatives.

Responsibilities:

• Identify relevant data sources - a combination of data sources to make it useful.
• Build the automation of the collection processes.
• Pre-processing of structured and unstructured data.
• Handle large amounts of information to create the input to analytical Models.
• Build predictive models and machine-learning algorithms Innovate Machine-Learning , Deep-Learning algorithms.
• Build Network graphs , NLP , Forecasting Models Building data pipelines for end-to-end solutions.
• Propose solutions and strategies to business challenges. Collaborate with product development teams and communicate with the Senior Leadership teams.
• Participate in Problem solving sessions

Requirements:

• Bachelor's degree in a highly quantitative field (e.g. Computer Science , Engineering , Physics , Math , Operations Research , etc) or equivalent experience.
• Extensive machine learning and algorithmic background with a deep level understanding of at least one of the following areas: supervised and unsupervised learning methods , reinforcement learning , deep learning , Bayesian inference , Network graphs , Natural Language Processing Analytical mind and business acumen
• Strong math skills (e.g. statistics , algebra)
• Problem-solving aptitude Excellent communication skills with ability to communicate technical information.
• Fluency with at least one data science/analytics programming language (e.g. Python , R , Julia).
• Start-up experience is a plus Ideally 5-8 years of advanced analytics experience in startups/marquee com

Required Skills:

Machine Learning, Deep Learning, Algorithms, Computer Science, Engineering, Operations Research, Math Skills, Communication Skills, SAAS Product, IT Services, Artificial Intelligence, ERP, Product Management, Automation, Analytical Models, Predictive Models, NLP, Forecasting Models, Product Development, Leadership, Problem Solving, Unsupervised Learning, Reinforcement Learning, Natural Language Processing, Algebra, Data Science, Programming Language, Python, Julia

About us

Skit (previously known as http://vernacular.ai/" target="_blank">Vernacular.ai) is an AI-first SaaS voice automation company. Its suite of speech and language solutions enable enterprises to automate their contact centre operations. With over 10 million hours of training data, its product - Vernacular Intelligent Voice Assistant (VIVA) can currently respond in 16+ languages, covering over 160+ dialects and replicating human-like conversations.

Skit currently serves a variety of enterprise clients across diverse sectors such as BFSI, F&B, Hospitality, Consumer Electronics and Travel & Tourism, including prominent clients like Axis Bank, Hathway, Porter and Barbeque Nation. It has been featured as one of the top-notch start-ups in the Cisco Launchpad’s Cohort 6 and is a part of the World Economic Forum’s Global Innovators Community. It has has also been listed in Forbes 30 Under 30 Asia start-ups 2021 for its remarkable industry innovation.

We are looking for ML Research Engineers to work on the following problems:

• Spoken Language Understanding and Dialog Management.
• Language semantics, parsing, and modeling across multiple languages.
• Speech Recognition, Speech Analytics and Voice Processing across multiple languages.
• Response Generation and Speech Synthesis.
• Active Learning, Monitoring and Observability mechanisms for deployments.

Responsibilities

• Design, build and evaluate Machine Learning solutions.
• Perform experiments and statistical analyses to draw conclusions and take modeling decisions.
• Study, implement and extend state of the art systems.
• Take part in regular research reviews and discussions.
• Build, maintain and extend our open source solutions in the domain.
• Write well-crafted programs at all levels of the system. This includes the data pipelines, experiment prototypes, fast and scalable deployment models, and evaluation, visualization and monitoring systems.

Requirements

• Practical Machine Learning experience as demonstrated by earlier works.
• Knowledge of and ability to use tools from theoretical and practical aspects of computer science. This includes, but is not limited to, probability, statistics, learning theory, algorithms, software architecture, programming languages, etc.
• Good programming skills and ability to work with programs at all levels of a finished Machine Learning product. We prefer language agnosticism since that exemplifies this point.
• Git portfolios and blogs are helpful as they let us better evaluate your work.

• What information we collect during our application and recruitment process and why we collect it;
• How we use that information; and
• How to access and update that information.

• Your name, address, email address, telephone number and other contact information;
• Your resume or CV, cover letter, previous and/or relevant work experience or other experience, education, transcripts, or other information you provide to us in support of an application and/or the application and recruitment process;
• Information from interviews and phone-screenings you may have, if any;
• Details of the type of employment you are or may be looking for, current and/or desired salary and other terms relating to compensation and benefits packages, willingness to relocate, or other job preferences;
• Details of how you heard about the position you are applying for;
• Reference information and/or information received from background checks (where applicable), including information provided by third parties;
• Information about your educational and professional background from publicly available sources, including online, that we believe is relevant to your application or a potential future application (e.g. your LinkedIn profile); and/or
• Information related to any assessment you may take as part of the interview screening process.

• Assessing your skills, qualifications and interests against our career opportunities;
• Verifying your information and carrying out reference checks and/or conducting background checks (where applicable) if you are offered a job;
• Communications with you about the recruitment process and/or your application(s), including, in appropriate cases, informing you of other potential career opportunities at Skit;
• Creating and/or submitting reports as required under any local laws and/or regulations, where applicable;
• Making improvements to Skit's application and/or recruitment process including improving diversity in recruitment practices;
• Proactively conducting research about your educational and professional background and skills and contacting you if we think you would be suitable for a role with us.