> HackerTyper Jobs

We are looking for a Senior Machine Learning Engineer to join our Knowledge Enrichment teamat BenchSci.
You will help design and implement ML-based approaches to analyse, extract and generateknowledge from complex biomedical data such as experimental protocols and from results fromseveral heterogeneous sources, including both publicly available data and proprietary internaldata, represented in unstructured text and knowledge graphs. You will work alongside some ofthe brightest minds in tech, leveraging state of the art approaches to deliver on BenchSci’smission to expedite drug discovery. Knowledge Enrichment is at the core of this challenge as itensures we can reason over and gain insights from an extensive, accurate, and high qualityrepresentation of biomedical data.
The data will be leveraged to enrich BenchSci’s knowledge graph through classification,discovery of high value implicit relationships, predicting novel insights/hypotheses, and other MLtechniques. You will collaborate with your team members in applying state of the art ML andgraph ML/data science algorithms to this data.
You are comfortable working in a team that pushes the boundaries of what is possible withcutting edge ML/AI, challenges the status quo, and is laser focused on value delivery in afail-fast environment.
Pay range: $160,000 - 200,000
We know compensation is an important part of choosing your next role. The range shown reflects our target hiring range, informed by market data, internal equity, and the role’s current scope. Often the mid-range is where we tend to fall, but individual offers may vary based on experience, skills, and the role scope.

You Will:

• Analize and manipulate a large, highly connected biological knowledge graph constructed of data from multiple heterogeneous sources, to identify data enrichment opportunities and strategies.
• Work with data and knowledge engineering experts to design and develop knowledge enrichment approaches/strategies that can exploit data within our knowledge graph.
• Provide solutions related to classification, clustering, more-like-this-type querying, discovery of high value implicit relationships, and making inferences across the data that can reveal novel insights.
• Deliver robust, scalable and production-ready ML models, with a focus on optimizing performance and efficiency.
• Architect and design ML solutions, from data collection and preparation, model selection, training, fine-tuning and evaluation, to deployment and monitoring.
• Collaborate with your teammates from other functions such as product management, project management and science, and other engineering disciplines.
• Sometimes provide technical leadership on Knowledge Enrichment projects that seek to use ML to enrich the data in BenchSci’s Knowledge Graph.
• Work closely with other ML engineers to ensure alignment on technical solutioning and approaches.
• Liaise closely with stakeholders from other functions including product and science.
• Help ensure adoption of ML best practices and state of the art ML approaches within your team(s).
• Participate in various agile rituals and related practices.

You Have:

• Minimum 3, ideally 5+ years of experience working as an ML engineer.
• Some experience providing technical leadership on complex projects.
• Degree, preferably PhD, in Software Engineering, Computer Science, or a similar area.
• A proven track record of delivering complex ML projects working alongside high performing ML, data and software engineers using agile software development.
• Demonstrable ML proficiency with a deep understanding of how to utilize state of the art NLP and ML techniques.
• Mastery of several ML frameworks and libraries, with the ability to architect complex ML systems from scratch. Extensive experience with Python and PyTorch.
• Track record of contributing to the successful delivery of robust, scalable and production-ready ML models, with a focus on optimizing performance and efficiency.
• Experience with the full ML development lifecycle from architecture and technical design, through data collection and preparation, model selection, training, fine-tuning and evaluation, to deployment and maintenance.
• Familiarity with implementing solutions leveraging Large Language Models, and a deep understanding of how to implement solutions using Retrieval Augmented Generation (RAG) architectures, including both Graph RAG and Vector RAG.
• Experience with graph machine learning (i.e. graph neural networks, graph data science) and practical applications thereof. Your experience working with Knowledge Graphs, ideally biological, and a familiarity with biological ontologies complement this.
• Experience with complex problem solving and an eye for details such as scalability and performance of a potential solution.
• Comprehensive knowledge of software engineering, programming fundamentals and industry experience using Python.
• Experience with data manipulation and processing, like SQL, Cypher or Pandas.
• A can-do, proactive and assertive attitude - your manager believes in freedom and responsibility and helping you own what you do. You will excel if this environment suits you.
• You have experience working in cross-functional teams with product managers, scientists, project managers, and engineers from other disciplines (e.g. data engineering).
• Ideally, you have worked in the scientific/biological domain with scientists on your team.
• Outstanding verbal and written communication skills. Can clearly explain complex technical concepts/systems to engineering peers and non-engineering stakeholders.
• A growth mindset continuously seeking to stay up-to-date with cutting-edge advances in ML/AI, complemented by actively engaging with the ML/AI community.

Benefits and Perks: * A great compensation package that includes BenchSci equity options* A robust  vacation policy plus an additional vacation day every year* Company closures for 14 more days throughout the year* Flex time for sick days, personal days, and religious holidays* Comprehensive health and dental benefits* Annual learning & development budget* A one-time home office set-up budget to use upon joining BenchSci* An annual lifestyle spending account allowance* Generous parental leave benefits with a top-up plan or paid time off options* The ability to save for your retirement coupled with a company match!

About BenchSci:

BenchSci's mission is to exponentially increase the speed and quality of life-saving research and development. We empower scientists to run more successful experiments with the world's most advanced, biomedical artificial intelligence software platform. 
Backed by Generation Investment Management, TCV, Inovia, F-Prime, Golden Ventures, and Google's AI fund, Gradient Ventures, we provide an indispensable tool for scientists that accelerates research at top pharmaceutical companies and leading academic centers.

Our Culture:

Our culture fosters transparency, collaboration, and continuous learning. 
We value each other's differences and always look for opportunities to embed equity into the fabric of our work. We foster diversity, autonomy, and personal growth, and provide resources to support motivated self-leaders in continuous improvement. 
You will work with high-impact, highly skilled, and intelligent experts motivated to drive impact and fulfill a meaningful mission. We empower you to unleash your full potential, do your best work, and thrive. Here you will be challenged to stretch yourself to achieve the seemingly impossible. 
####Diversity, Equity and Inclusion: We're committed to creating an inclusive environment where people from all backgrounds can thrive. We believe that improving diversity, equity and inclusion is our collective responsibility, and this belief guides our DEI journey.  Learn more about our DEI initiatives.
####Accessibility Accommodations: Should you require any accommodation, we will work with you to meet your needs. Please reach out to [email protected]. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.