Benefits:

• Equity

• Competitive pay

• Parental leave

• Home office allowance

• 401K (U.S.-based team members only) High-quality medical & vision insurance (U.S.-based team members only)

Experience Requirements:

• Experience with large language models or multimodal foundation models

• Knowledge of differential privacy and data anonymization techniques

• Experience with data ethics and bias detection

• Publications or research in synthetic data generation

Other Requirements:

• Understanding of scalable data processing architectures

Responsibilities:

• Design and implement comprehensive data generation strategies

• Develop synthetic data generation techniques

• Curate, clean, and validate large-scale real-world datasets

• Create advanced data augmentation and transformation pipelines

• Ensure data quality, ethical considerations, and bias mitigation

Benefits:

• Competitive compensation

• Medical, Vision and Dental coverage

• Flexible work environment and time-off policy

• 401k

• Company events

Education Requirements:

• Bachelors/Masters/PhD degree in Statistics, Mathematics or Computer Science, or another quantitative field

Experience Requirements:

• 8+ years of industry experience as a data scientist. For PhD degree holders, the minimum years of required experience as a data scientist is 6 years.

• 1+ years of management experience

Other Requirements:

• You have strong business sense, and are strong at defining good product KPIs/guardrail metrics, dashboarding and analysis of raw data to derive strategic insights.

• You are familiar with BI visualization tools such as Sigma, Metabase, Tableau or Looker.

• You are proficient in SQL and the modern data stack (e.g. dbt pipelines for ETL/ELT).

• You are proficient in Python.

• You have experience in writing source-controlled code for pipelines and internal tools for data-oriented decision making.

• You are strong at statistics. You have experience in applying these skills into tangible improvements in products, internal tools and processes using A/B testing and non-experimental methods.

• You are concise and precise in written and verbal communication. Technical documentation is your strong suit.

Responsibilities:

• Define and build data assets, e.g. KPI definitions, data pipelines and dashboards, to measure the performance of AI-powered assistant products for knowledge workers.

• Identify opportunities to improve these KPIs, and influence cross functional teams to incorporate associated changes into their roadmaps.

• Create and maintain quantitative frameworks and methodologies, e.g. bring more rigor into experiment analyses, use statistical modeling to identify leading indicators of user growth and engagement.

Benefits:

• Competitive compensation

• Medical, Vision and Dental coverage

• Flexible work environment and time-off policy

• 401k

• Company events

Education Requirements:

• Bachelors/Masters/PhD degree in Statistics, Mathematics or Computer Science, or another quantitative field

Experience Requirements:

• 5+ years of industry experience as a data scientist. For PhD degree holders, the minimum years of required experience as a data scientist is 2 years.

• You have strong business sense, and are strong at defining good product KPIs/guardrail metrics, dashboarding and analysis of raw data to derive strategic insights.

• You are familiar with BI visualization tools such as Sigma, Metabase, Tableau or Looker.

• You are proficient in SQL and the modern data stack (e.g. dbt pipelines for ETL/ELT).

• You are proficient in Python.You have experience in writing source-controlled code for pipelines and internal tools for data-oriented decision making.

Other Requirements:

• You are strong at statistics. You have experience in applying these skills into tangible improvements in products, internal tools and processes using A/B testing and non-experimental methods.

• You are concise and precise in written and verbal communication. Technical documentation is your strong suit.

Responsibilities:

• Define and build data assets, e.g. KPI definitions, data pipelines and dashboards, to measure the performance of AI-powered assistant products for knowledge workers.

• Identify opportunities to improve these KPIs, and influence cross functional teams to incorporate associated changes into their roadmaps.

• Create and maintain quantitative frameworks and methodologies, e.g. bring more rigor into experiment analyses, use statistical modeling to identify leading indicators of user growth and engagement.

Benefits:

• Competitive compensation

• Medical, Vision and Dental coverage

• Flexible work environment and time-off policy

• 401k

• Company events

Education Requirements:

• Bachelors/Masters/PhD degree in Statistics, Mathematics or Computer Science, or another quantitative field

Experience Requirements:

• 6+ years of industry experience (4+ for Masters degree holders, 3+ for PhD degree holders).

• You are concise and precise in written and verbal communication. Technical documentation is your strong suit.

• You are strong at defining good product KPIs/guardrail metrics, dashboarding and analysis of raw data to derive strategic insights.

• You are proficient in SQL and the modern data stack (e.g. dbt pipelines for ETL/ELT).

• You have experience in writing source-controlled code for pipelines and internal tools for data-oriented decision making.

Other Requirements:

• You’re strong in statistics and/or machine learning. You have experience in applying these skills into tangible improvements in products, internal tools and processes.

• You are proficient in Python.

Responsibilities:

• Define and build data assets, e.g. KPI definitions, data pipelines and dashboards, to measure the performance of AI-powered assistant products for knowledge workers.

• Identify opportunities to improve these KPIs, and influence cross functional teams to incorporate associated changes into their roadmaps.

• Create and maintain quantitative frameworks and methodologies, e.g. bring more rigor into experiment analyses, use statistical modeling to identify leading indicators of user churn & retention.

Education Requirements:

• PhD in Artificial Intelligence or Machine Learning

Other Requirements:

• Research / published papers in Auto ML, Neural Architecture Search, Personalization, or Forecasting

• Experience publishing at top conferences

• Able to write code and ideate with the product team

Responsibilities:

• Coming up with new techniques in unsupervised learning, dataset augmentation and deep reinforcement learning that can be applied to automating various parts of the AI development workflow

Benefits:

• Diverse projects across industries

• Competitive rates

• Comprehensive support from PMs

• Professional growth opportunities

• All-in-one platform for managing jobs and invoicing

Education Requirements:

• Third-level degree in Translation or Languages

• 2 years of translation experience plus any third-level degree

• 5 years of translation experience

Benefits:

• Competitive compensation

• Flexible work hours

• Health, dental, and vision insurance

• Commuter benefits

• Flexible PTO + holidays

Education Requirements:

• Master's degree in a related technical field or Bachelor's degree from a top-tier university with relevant work experience

Experience Requirements:

• Previous academic or work experience in deep learning

Other Requirements:

• Demonstrates a growth mindset and a passion for solving challenging problems

• Possesses academic or previous work experience in deep learning and distributed training of LLMs, Generative Models, and Transformers

• Experience with Pytorch, Python, and C++

• Familiarity with Speech Synthesis

• Experience with Direct Preference Optimization (DPO) and/or Reinforcement Learning from Human Feedback (RLHF)

Responsibilities:

• Designing and building large-scale data pipelines

• Experimenting and improving our Voice LLMs architectures for better quality, expressiveness, and latency

• Enhancing inference infrastructure to reduce costs and latency

• Scaling and optimizing LLM distributed training infrastructure

Benefits:

• Competitive compensation and equity

• Flexible work hours

• Health, dental, and vision insurance

• Commuter benefits

• Flexible PTO + holidays

Experience Requirements:

• An autonomous and resourceful engineer with a proven track record in deep learning

Other Requirements:

• Demonstrates a growth mindset and a passion for solving challenging problems

• Possesses hands-on experience in deep learning and distributed training of LLMs, Generative Models, and Transformers

• Experience with Pytorch, Python, and C++

• Familiarity with Speech Synthesis

Responsibilities:

• Designing and building large-scale data pipelines

• Experimenting and improving our Voice LLMs architectures for better quality, expressiveness, and latency

• Enhancing inference infrastructure to reduce costs and latency

• Scaling and optimizing LLM distributed training infrastructure

Experience Requirements:

• passion for adopting new research, tinkering with open source, and unlocking new creative possibilities with AI

Other Requirements:

• LLM Training / Inference

• Pytorch / CUDA

• Optimization (Pruning, Distillation, Kernel Fusion, etc.)

Education Requirements:

• Master’s degree in data analytics, business analytics, or a closely related field

Experience Requirements:

• 1 year of relevant data analytics experience

Other Requirements:

• Stats / ML

• A/B Testing

• Product Analytics

• SQL / Python

Responsibilities:

• Formulate hypotheses and apply rigorous analytical methodologies to validate them

• Use statistical analysis, ML, and data mining to uncover product insights

• Implement predictive models to guide product direction

• Define KPIs and develop dashboards to track performance

• Conduct A/B testing and experimental methods to measure feature impact

Benefits:

• Stock options (based on seniority level)

• Learning and development

• Health, dental, and vision insurance

• Paid time off

• Paid parental leave Wellness CoverageReferral bonus program

Experience Requirements:

• Proven Mid/Senior level experience as an ML engineer or a similar role

Responsibilities:

• Research, design, engineer, and support ML systems, including product research, algorithmic research, data preparation, coding, and fine-tuning based on QA feedback

• Leverage trade-offs between technical complexity and product requirements

• Be on top of related industry and research trends

• Communicate technical decisions effectively through technical discussions and design docs

Benefits:

• Competitive Salary

• WeWork membership for remote employees

• Annual Company Week Off (in addition to Vacation Policy)

• Birthday Off (in addition to Vacation Policy)

• Monthly fitness stipend

Experience Requirements:

• Attention to Detail

• Understanding of E-commerce Workflows

• Tech Savvy

• Communication Skills

• Good Time Management

Other Requirements:

• Background in E-commerce Customer Service (Preferred)

Responsibilities:

• Review and label e-commerce customer service conversations and policies with high accuracy.

• Collaborate with the AI and product teams to refine and optimize data labelling guidelines.

• Take ownership of data quality to improve AI model training.

• Work in collaboration with AI engineers to identify trends and nuances in customer service data that can be leveraged to fine-tune and improve our AI models.

• Manage the quality control process for labelled data, using a variety of modern tools and platforms for data processing and management, from advanced spreadsheets to AI-driven data labeling tools and project management systems.

Experience Requirements:

• Experience with Elasticsearch, Solr, Lucene, or other search engines.

• Experience with information retrieval techniques, ranking algorithms, and evaluation metrics, including but not limited to BM25, tf-idf, page rank, LTR models etc.

• Experience with machine learning and natural language processing and hands-on experience with clustering models, and recommendation models amongst others

• Experience with vector databases, embeddings, semantic and lexical retrieval techniques, metadata extraction, and enrichment

• This is a hands-on role and requires a builder mindset – design, develop and deploy. Distributed computing and deployment at scale

Responsibilities:

• Lead Neuron7.ai’s core AI/NLP technology that is at the heart of our service prediction engine

• Understand our clients’ data, identify signal from noise and build products that harness the intelligence in the signal

• Interface with customer teams in our key industries to truly understand use cases and datasets and solve for the prioritized product needs

• Collaborate with the product, engineering, leadership team in the company

• Build a team of data scientists and data engineers that consists of the best minds in applied AI in the Service domain

Experience Requirements:

• 7+ years

Other Requirements:

• Builder mindset: We are looking for individuals who are craving to create an impact in an AI-first Enterprise SaaS world.

• Ability to operate in a highly ambiguous and fast-paced environment. Passionate about creating and building new products.

• Experienced and talented NLP expert that has successfully rolled out Enterprise SaaS products in the CX space. Preferable Service.

• Experience across the enterprise NLP and data science spectrum – data engineering, data pipelines, process large Enterprise datasets, deep learning modules to learn from the signal in the dataset etc. and finally make predictions.

• Critical to have diverse heterogenous dataset experience – CRM data, Document/Manuals, Device data such as log files, ERP/Engineering datasets, IoT etc.

• Expertise in data modeling and ontology detection techniques

• A good combination of startup experience + a large enterprise company mix is a huge plus.

• Experience in rolling out NLP products in production for verticals such as High Tech, Medical device, Industrial appliance, High Tech manufacturing is great to have

Responsibilities:

• Lead Neuron7.ai’s core AI/NLP technology that is at the heart of our service prediction engine

• Understand our clients’ data, identify signal from noise and build products that harness the intelligence in the signal

• Interface with customer teams in our key industries to truly understand use cases and datasets and solve for the prioritized product needs

• Collaborate with the product, engineering, leadership team in the company

• Build a team of data scientists and data engineers that consists of the best minds in applied AI in the Service domain

Benefits:

• Entrepreneurial and inclusive culture

• Excellent health coverage

• Four weeks paid vacation

• Catered lunches twice a week over machine learning talks

• Opportunities to collaborate with faculty at the Vector Institute

Education Requirements:

• BSc+ in Computer Science, Math, Physics, or similar

• PhD or Master’s degree in Computer Science, Statistics, Mathematics, Engineering or a related field

Experience Requirements:

• 3+ Years of industry experience as a Software Engineer leading the development of features

• Experience with building and scaling data-intensive software.

• 2+ years of research experience with publication record

• 2+ years of extensive programming experience, 1+ year experience of building machine learning production system

Other Requirements:

• Experience with building a library or a framework.

• Experience with Big Data technologies and frameworks including but not limited to Spark, Cassandra, Kafka.

• Experience with Microsoft Azure

• Comfortable with statistics.

• Knowledge of machine learning and deep learning.

• Knowledge of distributed systems.

• Strong background in machine learning and deep learning

• Proven track record of applying machine learning to solve real-world problems

• Depth of experience in relevant ML research disciplines

• Hands on experience in software systems development

• Experience with one or more of Pytorch, Tensorflow, Jax, or comparable library

• Experience with Spark, SQL, or comparable database systems

• Experience using GPUs for accelerated deep learning training

• Familiarity with cloud computing systems like Azure or AWS

• Strong communication, business acumen and stakeholder management competencies

• Strong technical skills: machine learning, data engineering, MLOps, cloud solution architecture, software development practices

• Strong coding proficiency: python, R, SQL and / or Scala, cloud architecture

• Certified Scrum Product Owner and / or Certified Scrum Master or equivalent experience

• Familiarity with cloud solution architecture, Azure a plus

• Solid knowledge of applied Machine Learning, Deep Learning, Large Language Models

• Experience with developing MLOps CI/CD pipelines for deploying AI/ML models

• Solid cloud experience with Azure or AWS and cloud AI/ML services such as Databricks, Kubernetes, docker and container orchestration, Azure Machine Learning, Azure Data Factory

• Strong experience with PySpark for big data processing and PyTorch for deep learning model serving

• Expert coder with Python, Java, or Scala

• Experience with RAG, LLM fine tuning, LLM serving

• Practical expertise in performance tuning, bottleneck problems analysis, and troubleshooting

• Knowledge of cloud engineering

• Self-motivated and demonstrated ability to take independent action to delivery results.

• Highly developed critical thinking, analytical and problem-solving skills

• Strong verbal and written communication skills, with the ability to work effectively across teams

Responsibilities:

• Own and ship product features that enable ML engine capabilities.

• Work with product owners and tech leads to design, ship, and refine significant components of the product.

• Work with scientists and MLOps teams to maintain and service the product.

• Translate broad business problems into sharp data science use cases, and craft use cases into product visions

• Own machine learning products from vision to backlog; prioritizing features and defining minimum viable releases; maximizing the value your products generate, and the ROI of your pod