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Akaike Technologies - Lead Data Scientist - Machine Learning/NLP (4-8 yrs) | Scientist in Science 1

Akaike Technologies

This listing was posted on hirist.

Akaike Technologies - Lead Data Scientist - Machine Learning/NLP (4-8 yrs)

Location:
Bangalore
Description:

About the job : At Akaike Technologies, we foster unique career paths with an inclusive culture, extensive support, and cutting-edge technology. Join our team to shape the future with Vision AI and positively impact the quality of life on our planet.Responsibilities : - Analyse raw data : assessing quality, cleansing, and structuring for downstream processing - Design efficient and scalable AI solutions for a wide range of problems that generate actionable insights or automate the existing process- Collaborate with the Data engineers, UI, and backend engineers to bring analytical prototypes to production- Work with cross-functional teams to identify and understand business problems and develop data-driven solutions- Communicate findings and insights to technical and non-technical stakeholders clearly and concisely- Contribute or drive hiring, training & onboarding of new members to the team.- Participate in peer review of code and other technical work to ensure high-quality deliverables- Stay up-to-date with the latest developments and trends in data science, machine learning, deep learning, NLP/LLMs, and applied ML domainsQualifications : - At least 4 years of experience developing machine-learning methods - At least 3 years of experience building Deep learning models in NLP, CV, or other domains- Deep understanding of data analysis, machine learning, deep learning, clustering and classification techniques, and algorithms- Fluency with Python, Database(MySQL/Postgres/MongoDB), Git versioning, Data Analysis Libraries(NumPy, Pandas, Statsmodels, Dask), Machine Learning Libraries( Scikit-learn), Deep Learning Libraries(Tensorflow/Keras/Pytorch), Data Visualization Libraries(Matplotlib, Plotly)- Understanding of and experience with NLP, CV, and Deep learning techniques including Word2vec, NER, topic modeling, ConvNets/ResNets/UNet, Mask-RCNN, RNNs/LSTMs, Transformers/BERT/T5/GPT-4, large-scale pretraining, contrastive learning, DL architecture design, and LLM finetuning among others.- Experience utilizing large-scale language models such as GPT-4 or other open-source alternatives (such as Mistral, Llama, and Phi-1) through prompt engineering and custom finetuning.- Familiarity with Big Data frameworks and visualization tools (Cassandra, Hadoop, Spark, Tableau)- Deep familiarity with at least one cloud platform and its tools for developing solutions and deployment eg. AWS, Azure, or Google Cloud Platform- Experience leading a team of data scientists, architecting solutions, and devising project plans- Experience driving client engagement and problem discovery for multiple clients- Ability to manage multiple projects simultaneously and deliver results on time- Strong communication skills and experience working with cross-functional teamsOptional and preferred qualifications : - Experience publishing and presenting work at conferences, seminars, and workshops- Experience collaborating cross-functionally with other departments including hiring, marketing, pre-sales, and R&D- Experience hiring and leading Senior Data Scientists- Experience ideating and implementing platforms and products for accelerated Data Science solutions- Experience working in a startup as an initial core contributorBenefits and Perks : - Competitive ESOP grants with faster vesting periods- Leading a team and working on services & initiatives independently- Profit & Loss (P&L) responsibility making incentives completely transparent- An opportunity for hiring & training people to drive the value they create- Opportunity and budget to go to networking events, conferences, and seminars- Visibility on all the functions at Akaike including sales, pre-sales, lead generation, marketing, and hiring (ref:hirist.tech)
Education/experience:
2 To 5 Years
Company:
Akaike Technologies
Posted:
May 10 on hirist
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